diff --git a/README.md b/README.md
index 7c0700d..bd9cbb9 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,7 @@ Measurement and automation of the Bechdel test, female (under)representation and
- Official documentation is at https://dataforgood.fr/bechdelai
- Official website for the project is here (French) - https://dataforgood.fr/projects/bechdelai
- Project documentation is [here](https://dataforgood.slite.com/app/docs/~8IRrgyKYR) (French)
-
+- For audio projects, details are [here](notebooks/audio/README.md)
## Developers
diff --git a/app.py b/app.py
new file mode 100644
index 0000000..17bf6bd
--- /dev/null
+++ b/app.py
@@ -0,0 +1,125 @@
+# Inspired from https://huggingface.co/spaces/vumichien/whisper-speaker-diarization/blob/main/app.py
+
+import gradio as gr
+import re
+import time
+import os
+
+import pandas as pd
+import numpy as np
+import sys
+sys.path.append("../../")
+
+from pytube import YouTube
+
+# Custom code
+from bechdelai.data.youtube import download_youtube_video
+from bechdelai.audio.utils import extract_audio_from_video
+from bechdelai.audio.gender_segmenter import InaSpeechSegmentor
+from bechdelai.audio.transcriber import WhisperAPI
+from bechdelai.nlp.gpt import GPT3
+
+# Constants
+# whisper_models = ["tiny.en","base.en","tiny","base", "small", "medium", "large"]
+# device = 0 if torch.cuda.is_available() else "cpu"
+# os.makedirs('output', exist_ok=True)
+
+def get_youtube(video_url):
+ yt = YouTube(video_url)
+ abs_video_path = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first().download()
+ print("Success download video")
+ print(abs_video_path)
+ return abs_video_path
+
+
+def speech_to_text(video_filepath, selected_source_lang = "en", whisper_model = "tiny.en"):
+ """
+ # Transcribe youtube link using OpenAI Whisper
+ 1. Using Open AI's Whisper model to seperate audio into segments and generate transcripts.
+ 2. Generating speaker embeddings for each segments.
+ 3. Applying agglomerative clustering on the embeddings to identify the speaker for each segment.
+
+ Speech Recognition is based on models from OpenAI Whisper https://github.com/openai/whisper
+ Speaker diarization model and pipeline from by https://github.com/pyannote/pyannote-audio
+ """
+
+ whisper_api = WhisperAPI()
+ gender = InaSpeechSegmentor(only_gender=True,batch_size = 32)
+
+ # Convert video to audio
+ audio_filepath = extract_audio_from_video(video_filepath,"mp3")
+ result,segments,text = whisper_api.speech_to_text(audio_filepath)
+ segments_ina = gender._convert_whisper_output(segments)
+ segments_ina = gender.predict_gender_on_segments(audio_filepath,segments_ina)
+ segments_with_gender = segments.merge(segments_ina[["gender","start"]],on = "start",how = "left")
+
+ dialogue_id = segments_with_gender["speech"].astype(int).diff(1).fillna(0)
+ dialogue_id.loc[dialogue_id < 0] = 0
+ segments_with_gender["dialogue_id"] = dialogue_id.cumsum()
+ segments_with_gender.loc[segments_with_gender["speech"] == False,"dialogue_id"] = np.NaN
+
+ return [segments_with_gender,text]
+
+source_language_list = ["en","fr"]
+
+# ---- Gradio Layout -----
+# Inspiration from https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles
+video_in = gr.Video(label="Video file", mirror_webcam=False)
+youtube_url_in = gr.Textbox(label="Youtube url", lines=1, interactive=True)
+# selected_source_lang = gr.Dropdown(choices=source_language_list, type="value", value="en", label="Spoken language in video", interactive=True)
+# selected_whisper_model = gr.Dropdown(choices=whisper_models, type="value", value="tiny.en", label="Selected Whisper model", interactive=True)
+df_init = pd.DataFrame(columns=['start', 'end', 'text', 'speech', 'gender', 'duration', 'dialogue_id'])
+transcription_df = gr.DataFrame(value = df_init,label="RΓ©partition du temps de parole", row_count=(0, "dynamic"), max_rows = 25, wrap=True, overflow_row_behaviour='paginate')
+output_text = gr.Textbox(label = "Transcribed text",lines = 10)
+
+title = "BechdelAI - demo"
+demo = gr.Blocks(title=title,live = True)
+demo.encrypt = False
+
+
+with demo:
+ with gr.Tab("BechdelAI - dialogue demo"):
+ gr.Markdown('''
+
+
BechdelAI - Dialogue demo
+
+ ''')
+
+ with gr.Row():
+ gr.Markdown('''# π₯ Download Youtube video''')
+
+
+ with gr.Row():
+
+ with gr.Column():
+ # gr.Markdown('''### You can test by following examples:''')
+ examples = gr.Examples(examples=
+ [
+ "https://www.youtube.com/watch?v=FDFdroN7d0w",
+ "https://www.youtube.com/watch?v=b2f2Kqt_KcE",
+ "https://www.youtube.com/watch?v=ba5F8G778C0",
+ ],
+ label="Examples", inputs=[youtube_url_in])
+ youtube_url_in.render()
+ download_youtube_btn = gr.Button("Download Youtube video")
+ download_youtube_btn.click(get_youtube, [youtube_url_in], [
+ video_in])
+ print(video_in)
+
+ with gr.Column():
+ video_in.render()
+
+ with gr.Row():
+ gr.Markdown('''# π Extract text from video''')
+
+ with gr.Row():
+ with gr.Column():
+ transcribe_btn = gr.Button("Transcribe audio and diarization")
+ # transcribe_btn.click(speech_to_text, [video_in, selected_source_lang, selected_whisper_model], [transcription_df,output_text])
+ transcribe_btn.click(speech_to_text, [video_in], [transcription_df,output_text])
+ with gr.Column():
+ output_text.render()
+ with gr.Row():
+ transcription_df.render()
+
+demo.launch(debug=True)
\ No newline at end of file
diff --git a/bechdelai/audio/audio_processor.py b/bechdelai/audio/audio_processor.py
new file mode 100644
index 0000000..73d88f8
--- /dev/null
+++ b/bechdelai/audio/audio_processor.py
@@ -0,0 +1,39 @@
+import pandas as pd
+
+
+class AudioProcessor:
+ """Computes complete pipeline from audio to text format dialogues
+ gendered_audio_seg represents gender identification + voice activity detection
+ feminine_dialogues aims to keep only dialogues where women are speaking
+ result transforms selected audios into text
+ """
+ def __init__(self, config, audio_file=""):
+ self.audio = audio_file
+ self.config = config
+ self.gendered_audio_seg = self.gender_segmentor()
+ self.feminine_dialogues = self.dialogue_tagger()
+ self.result = self.run_speech_to_text()
+
+ def gender_segmentor(self):
+ return self.config.get_profile().get_gender_segmentor().segment(self.audio)
+
+ def dialogue_tagger(self):
+ return self.config.get_profile().get_dialogue_tagger().extract_dialogues_subsets(self.gendered_audio_seg)
+
+ def run_speech_to_text(self):
+ transcript = []
+ for i in self.feminine_dialogues.index:
+ duration = self.feminine_dialogues['end'][i] - self.feminine_dialogues['start'][i]
+ transcript.append(self.config.get_profile().get_transcriber().speech_to_text(self.audio,
+ self.gendered_audio_seg['start'][i],
+ duration))
+ transcription = pd.concat([self.gendered_audio_seg['gender'], pd.Series(transcript, name="transcription")],
+ axis=1)
+ return transcription
+
+ def full_dataframe(self):
+ return pd.concat([self.gendered_audio_seg, self.result['transcription']], axis=1)
+
+ def export_to_csv(self, file_path: str):
+ result = self.full_dataframe()
+ result.to_csv(path_or_buf=file_path, sep=";", header=True, index=False, encoding="utf-8")
diff --git a/bechdelai/audio/audio_separation.py b/bechdelai/audio/audio_separation.py
new file mode 100644
index 0000000..4de0d1d
--- /dev/null
+++ b/bechdelai/audio/audio_separation.py
@@ -0,0 +1,14 @@
+def separate_voice_and_music(path_to_mixed_audio: str) -> None:
+ """Splits an audio file into its individual parts using spleeter
+
+ Does not work above 700 seconds or about 11 minutes.
+
+ Stores the results in separate folders, upstream of the project root.
+
+ Parameters:
+ path_to_mixed_audio (str): Path to an audio file (.wav)
+
+ Returns:
+ None
+ """
+ os.system('spleeter separate -d 700.0 -o ../../../ -f "{instrument}/{filename}.{codec}" ' + path_to_mixed_audio)
diff --git a/bechdelai/audio/config.py b/bechdelai/audio/config.py
new file mode 100644
index 0000000..582ba80
--- /dev/null
+++ b/bechdelai/audio/config.py
@@ -0,0 +1,15 @@
+from . import profiles
+
+
+class Config:
+ def __init__(self):
+ self.selected_profile: profiles.Profiles
+
+ def select_profile(self, option):
+ if option == "FR":
+ self.selected_profile = profiles.French()
+ elif option == "US":
+ self.selected_profile = profiles.USEnglish()
+
+ def get_profile(self):
+ return self.selected_profile
diff --git a/bechdelai/audio/dialogue_tagger.py b/bechdelai/audio/dialogue_tagger.py
new file mode 100644
index 0000000..9c1c6f5
--- /dev/null
+++ b/bechdelai/audio/dialogue_tagger.py
@@ -0,0 +1,18 @@
+from abc import ABC, abstractmethod
+
+
+class DialogueTagger(ABC):
+ """Abstract Class common to every gender segmentor.
+ Convert an audio file to a dataframe of time slots associated with the speaker's gender.
+ """
+ @abstractmethod
+ def extract_dialogues_subsets(self, segments_dataframe):
+ pass
+
+
+class RuleBasedTagger(DialogueTagger):
+ def __init__(self):
+ pass
+
+ def extract_dialogues_subsets(self, segments_dataframe):
+ return segments_dataframe
diff --git a/bechdelai/audio/gender_segmenter.py b/bechdelai/audio/gender_segmenter.py
new file mode 100644
index 0000000..312fbb4
--- /dev/null
+++ b/bechdelai/audio/gender_segmenter.py
@@ -0,0 +1,58 @@
+import pandas as pd
+from abc import ABC, abstractmethod
+from inaSpeechSegmenter import Segmenter
+from inaSpeechSegmenter.segmenter import Gender
+from inaSpeechSegmenter.features import media2feats
+
+
+class GenderSegmentor(ABC):
+ """Abstract Class common to every gender segmentor.
+ Convert an audio file to a dataframe of time slots associated with the speaker's gender.
+ """
+ @abstractmethod
+ def segment(self, audio_file):
+ pass
+
+CONSTANT_INA = 0.02
+
+class InaSpeechSegmentor(GenderSegmentor):
+ def __init__(self,only_gender = False,batch_size = 32):
+ # The higher the energy ratio, the more selective it is ; vad_engine works better with sm than smn
+ if not only_gender:
+ self.seg = Segmenter(vad_engine='sm', energy_ratio=0.05)
+ else:
+ self.gender = Gender(batch_size = batch_size)
+
+ def segment(self, audio_file):
+ """Extracts time intervals from audio_file, according to the speaker's gender.
+
+ Returns:
+ pd.DataFrame: Pandas' DataFrame with 3 columns (gender, start, end) and as many lines as needed.
+ """
+ segment = self.seg(audio_file)
+ return pd.DataFrame(list(filter(lambda x: x[0] == 'male' or x[0] == 'female', segment)),
+ columns=['gender', 'start', 'end'])
+
+
+ def _convert_whisper_output(self,segments:pd.DataFrame) -> list:
+ segments = segments.query("speech").assign(category = lambda x : "speech")[["category","start","end"]]
+ convert_to_ina_format = lambda x : int(x/CONSTANT_INA)
+ segments["start"] = segments["start"].map(convert_to_ina_format)
+ segments["end"] = segments["end"].map(convert_to_ina_format)
+ segments = [tuple(x) for x in segments.to_numpy()]
+ return segments
+
+ def predict_gender_on_segments(self,audio_file,segments):
+
+ mspec, loge, difflen = media2feats(audio_file, None,0,None,"ffmpeg")
+ segments = self.gender(mspec, segments, difflen)
+
+ segments_df = pd.DataFrame(segments,columns = ["gender","start","end"])
+ segments_df["start"] = segments_df["start"] * CONSTANT_INA
+ segments_df["end"] = segments_df["end"] * CONSTANT_INA
+ return segments_df
+
+
+
+
+
diff --git a/bechdelai/audio/profiles.py b/bechdelai/audio/profiles.py
new file mode 100644
index 0000000..fcf7b2f
--- /dev/null
+++ b/bechdelai/audio/profiles.py
@@ -0,0 +1,41 @@
+""" Profiles are used to set the adapted configuration to analyse the video of interest.
+"""
+from abc import ABC, abstractmethod
+
+from . import transcriber, gender_segmenter, dialogue_tagger
+
+
+class Profiles(ABC):
+ @abstractmethod
+ def get_gender_segmentor(self):
+ raise "Gender Segmentor not implemented"
+
+ @abstractmethod
+ def get_dialogue_tagger(self):
+ raise "Dialogue tagger not implemented"
+
+ @abstractmethod
+ def get_transcriber(self):
+ raise "Transcriber not implemented"
+
+
+class French(Profiles):
+ def get_gender_segmentor(self):
+ return gender_segmenter.InaSpeechSegmentor()
+
+ def get_dialogue_tagger(self):
+ return dialogue_tagger.RuleBasedTagger()
+
+ def get_transcriber(self):
+ return transcriber.GoogleSpeechRecognition("fr-FR")
+
+
+class USEnglish(Profiles):
+ def get_gender_segmentor(self):
+ return gender_segmenter.InaSpeechSegmentor()
+
+ def get_dialogue_tagger(self):
+ return dialogue_tagger.RuleBasedTagger()
+
+ def get_transcriber(self):
+ return transcriber.GoogleSpeechRecognition("en-US")
diff --git a/bechdelai/audio/transcriber.py b/bechdelai/audio/transcriber.py
new file mode 100644
index 0000000..110e8cd
--- /dev/null
+++ b/bechdelai/audio/transcriber.py
@@ -0,0 +1,82 @@
+import os
+import pandas as pd
+import speech_recognition as sr
+import openai
+import whisper
+from dotenv import load_dotenv
+from abc import ABC, abstractmethod
+
+
+class Transcriber(ABC):
+ # Abstract Class common to every transcriber model.
+ # Possibility to deal with audio ranges of a certain duration.
+ def __init__(self):
+ pass
+
+ @abstractmethod
+ def speech_to_text(self, audio_file, start_time, duration):
+ pass
+
+
+class GoogleSpeechRecognition(Transcriber):
+ # Recognize speech using Google Speech Recognition
+ def __init__(self, language):
+ self.language = language
+ self.r = sr.Recognizer()
+
+ def read(self, audio_file, start_time=None, duration=None):
+ with sr.AudioFile(audio_file) as source:
+ return self.r.record(source, duration=duration, offset=start_time)
+
+ def speech_to_text(self, audio_file, start_time, duration):
+ audio = self.read(audio_file, start_time-1, duration+2)
+ try:
+ return self.r.recognize_google(audio, language=self.language) # It may be necessary to change the API key
+ except sr.UnknownValueError:
+ print("Google Speech Recognition could not understand audio")
+ except sr.RequestError as e:
+ print("Could not request results from Google Speech Recognition service; {0}".format(e))
+
+
+class WhisperAPI(Transcriber):
+ def __init__(self,api_key = None):
+
+ # Set up API key
+ if api_key is None:
+ try:
+ load_dotenv()
+ api_key = os.environ["OPENAI_API_KEY"]
+ except:
+ raise Exception("No OpenAI key was found in the environment or in a .env file")
+
+ assert api_key.startswith("sk-")
+ openai.api_key = api_key
+
+ def speech_to_text(self,audio_file,response_format = "verbose_json"):
+ # From https://openai.com/blog/introducing-chatgpt-and-whisper-apis
+ # Doc at https://platform.openai.com/docs/guides/speech-to-text
+ # TODO should add test if file > 25mb -> fails with openAI API, use mp3 and not wav as safety check
+ file = open(audio_file, "rb")
+ result = openai.Audio.transcribe("whisper-1", file,response_format = response_format)
+ segments = pd.DataFrame([dict(x) for x in result["segments"]])[["start","end","text"]]
+ segments["text"] = segments["text"].str.strip()
+ segments["speech"] = segments["text"].map(lambda x : x != "βͺβͺ")
+ text = result["text"]
+ return result,segments,text
+
+
+class Whisper(Transcriber):
+ def __init__(self,model_name = "tiny.en"):
+ assert model_name in ["tiny.en","base.en","tiny","base", "small", "medium", "large"]
+ self.model = whisper.load_model(model_name)
+
+ def speech_to_text(self,audio_file,language = "en"):
+
+ options = dict(language=language, beam_size=5, best_of=5)
+ transcribe_options = dict(task="transcribe", **options)
+ result = self.model.transcribe(audio_file, **transcribe_options)
+ segments = result["segments"]
+ text = result["text"].strip()
+
+ return result,segments,text
+
diff --git a/bechdelai/audio/utils.py b/bechdelai/audio/utils.py
new file mode 100644
index 0000000..db1d9c9
--- /dev/null
+++ b/bechdelai/audio/utils.py
@@ -0,0 +1,47 @@
+import os
+
+import moviepy.editor as mp
+from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip
+
+
+def cut_and_save(movie_path: str, start: float, end: float, target_name: str) -> None:
+ """This function cuts a video from the start to the end time and saves it as target_name.
+
+ Parameters:
+ movie_path (str): The path to the video file.
+ start (float): The start time in seconds.
+ end (float): The end time in seconds.
+ target_name (str): The file name of the new video file.
+
+ Returns:
+ None
+ """
+ return ffmpeg_extract_subclip(movie_path, start, end, targetname=target_name)
+
+
+def import_as_clip(path_to_video: str) -> mp.VideoFileClip:
+ """Imports a video file as a VideoFileClip object.
+
+ Parameters:
+ path_to_video (str): Path to a video file.
+
+ Returns:
+ mp.VideoFileClip: VideoFileClip object.
+ """
+ return mp.VideoFileClip(path_to_video)
+
+
+
+
+def extract_audio_from_video(file: str, extension: str = 'wav') -> None:
+ """Extract the audio from a film and save it to a file.
+
+ The audio is saved in the same directory as the film.
+
+ Parameters:
+ file (str): The name of the film file to extract the audio from.
+ extension (str): The file extension of the audio file to save (default is ".wav").
+ """
+ assert extension in ["wav","mp3"]
+ clip = import_as_clip(file)
+ clip.audio.write_audiofile(f"{file.split(sep='.')[0]}.{extension}")
diff --git a/bechdelai/data/youtube.py b/bechdelai/data/youtube.py
index 4e595cb..bc2832a 100644
--- a/bechdelai/data/youtube.py
+++ b/bechdelai/data/youtube.py
@@ -1,7 +1,13 @@
from pytube import YouTube
+import urllib.parse as urlparse
+try:
+ from IPython.display import display,HTML
+except:
+ print("Jupyter is not installed, you may encounter a few errors")
-def download_youtube_video(link: str, filename: str, caption_language: str) -> None:
+
+def download_youtube_video(link: str, filename: str, download_captions:bool = False,caption_language: str = "en") -> None:
"""Download a youtube video with captions given an id
Parameters
@@ -26,25 +32,67 @@ def download_youtube_video(link: str, filename: str, caption_language: str) -> N
print("Connection Error")
return
+ filename = filename if filename.endswith(".mp4") else filename + ".mp4"
+
try:
(
yt.streams.filter(progressive=True, file_extension="mp4")
.order_by("resolution")
.desc()
.first()
- ).download(filename=f"{filename}.mp4")
+ ).download(filename=filename)
+
+ print(f"Saved the youtube video at {filename}")
except Exception as e:
print("Could not download the video!", e)
- try:
- captions = {
- k: v
- for k, v in yt.captions.lang_code_index.items()
- if caption_language in k
- }
- for lang, caption in captions.items():
- caption.download(title=f"caption_{lang}", srt=False)
- except Exception as e:
- print("Could not download the caption!", e)
- print("Task Completed!")
+ if download_captions:
+ try:
+ captions = {
+ k: v
+ for k, v in yt.captions.lang_code_index.items()
+ if caption_language in k
+ }
+ for lang, caption in captions.items():
+ caption.download(title=f"caption_{lang}", srt=False)
+ except Exception as e:
+ print("Could not download the caption!", e)
+ print("Task Completed!")
+
+
+def get_youtube_video_id_from_url(url):
+ """
+ From https://stackoverflow.com/questions/48072619/how-can-i-import-urlparse-in-python-3
+ Examples:
+ - http://youtu.be/SA2iWivDJiE
+ - http://www.youtube.com/watch?v=_oPAwA_Udwc&feature=feedu
+ - http://www.youtube.com/embed/SA2iWivDJiE
+ - http://www.youtube.com/v/SA2iWivDJiE?version=3&hl=en_US
+ """
+ query = urlparse.urlparse(url)
+ if query.hostname == 'youtu.be':
+ return query.path[1:]
+ if query.hostname in ('www.youtube.com', 'youtube.com'):
+ if query.path == '/watch':
+ p = urlparse.parse_qs(query.query)
+ return p['v'][0]
+ if query.path[:7] == '/embed/':
+ return query.path.split('/')[2]
+ if query.path[:3] == '/v/':
+ return query.path.split('/')[2]
+ # fail?
+ return None
+
+
+def show_youtube_in_notebook(url):
+
+ video_id = get_youtube_video_id_from_url(url)
+
+ html = f"""
+
+ VIDEO
+
+ """
+
+ display(HTML(html))
\ No newline at end of file
diff --git a/bechdelai/nlp/gpt.py b/bechdelai/nlp/gpt.py
new file mode 100644
index 0000000..64aee6d
--- /dev/null
+++ b/bechdelai/nlp/gpt.py
@@ -0,0 +1,64 @@
+import pandas as pd
+import openai
+from dotenv import load_dotenv
+import os
+
+
+class GPT3:
+ def __init__(self,api_key = None):
+
+ # Set up API key
+ if api_key is None:
+ try:
+ load_dotenv()
+ api_key = os.environ["OPENAI_API_KEY"]
+ except:
+ raise Exception("No OpenAI key was found in the environment or in a .env file")
+
+ assert api_key.startswith("sk-")
+ openai.api_key = api_key
+
+ def generate(self,prompt,model = "text-davinci-003",max_tokens = 256,temperature = 0.7):
+
+ response = openai.Completion.create(
+ model=model,
+ prompt=prompt,
+ temperature=temperature,
+ max_tokens=max_tokens,
+ top_p=1,
+ frequency_penalty=0,
+ presence_penalty=0
+ )
+ try:
+ return response["choices"][0]["text"]
+ except:
+ return response
+
+
+ def make_prompt(self,question,dialogue):
+ prompt = f"""
+ Dialogue:
+ {dialogue}
+ -------------------------------
+ You are a social scientist, feminist and expert in gender representation in cinema and in culture.
+ You know everything about the Bechdel test and study gender and ethnic inequalities, in particular how women are represented in movies and the stereotypes shown onscreen
+
+ Please answer the following question about the dialogue above by detailing your reasoning
+
+ Question: {question}
+ Answer:
+ """
+ return prompt
+
+ def answer_questions(self,questions,dialogue,**kwargs):
+
+ if isinstance(questions,str): questions = [questions]
+
+ answers = []
+
+ for question in questions:
+ prompt = self.make_prompt(question,dialogue)
+ answer_question = self.generate(prompt,**kwargs)
+ answers.append({"question":question,"answer":answer_question})
+ answers = pd.DataFrame(answers)
+ return answers
\ No newline at end of file
diff --git a/notebooks/audio/audio_recognition_test.ipynb b/notebooks/audio/audio_recognition_test.ipynb
deleted file mode 100644
index 98a2df3..0000000
--- a/notebooks/audio/audio_recognition_test.ipynb
+++ /dev/null
@@ -1,1076 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Imports"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "import moviepy.editor as mp\n",
- "import speech_recognition as sr\n",
- "from inaSpeechSegmenter import Segmenter\n",
- "from inaSpeechSegmenter.export_funcs import seg2csv, seg2textgrid\n",
- "import os\n",
- "import pandas as pd\n",
- "from tqdm import tqdm\n",
- "tqdm.pandas()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Process 1 : Extraire l'audio d'une video"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "path_to_the_video = os.path.abspath(os.path.join(os.getcwd(),os.pardir,'data','sample_videos','cousinade_court_mΓ©trage.mp4'))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "my_clip = mp.VideoFileClip(path_to_the_video)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "#Extract the audio\n",
- "path_to_audio = os.path.abspath(os.path.join(path_to_the_video, os.pardir, 'cousinade_audio.wav'))\n",
- "#my_clip.audio.write_audiofile(path_to_audio)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Process 2 : Extraire le texte"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "def decodeSpeech(wavefile, start_time = None, end_time = None, language = None):\n",
- " \n",
- " r = sr.Recognizer()\n",
- " #r.pause_threshold = 3\n",
- " #r.dynamic_energy_adjustment_damping = 0.5\n",
- "\n",
- " with sr.WavFile(wavefile) as source:\n",
- " if start_time == None and end_time == None:\n",
- " audio_text = r.record(source)\n",
- " else:\n",
- " audio_text = r.record(source, duration = end_time - start_time, offset = start_time)\n",
- " \n",
- " if language == None: #default language is American English\n",
- " lg = \"en-US\"\n",
- " else:\n",
- " lg = language\n",
- "\n",
- " # recoginize_() method will throw a request error if the API is unreachable, hence using exception handling\n",
- " try:\n",
- " \n",
- " # using google speech recognition\n",
- " text = r.recognize_google(audio_text, language = lg)\n",
- " print('Converting audio transcripts into text ...')\n",
- " return text\n",
- " \n",
- " except:\n",
- " print('Sorry.. run again...')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [],
- "source": [
- "language = \"fr-FR\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "seg = Segmenter()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "segmentation = seg(path_to_audio)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [],
- "source": [
- "mapper = {'source' : [], 'start_time' : [] , 'end_time' : [] }\n",
- "for seg in segmentation:\n",
- " mapper['source'].append(seg[0])\n",
- " mapper['start_time'].append(seg[1])\n",
- " mapper['end_time'].append(seg[2])\n",
- " "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {},
- "outputs": [],
- "source": [
- "df = pd.DataFrame(mapper)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "female 29\n",
- "male 24\n",
- "noise 15\n",
- "noEnergy 8\n",
- "music 3\n",
- "Name: source, dtype: int64"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.source.value_counts()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [],
- "source": [
- "df['text'] = ''"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- " 7%|ββββββ | 2/29 [00:10<02:19, 5.17s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 10%|βββββββββ | 3/29 [00:14<02:06, 4.85s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 14%|ββββββββββββ | 4/29 [00:16<01:29, 3.58s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 17%|βββββββββββββββ | 5/29 [00:16<01:00, 2.54s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 21%|ββββββββββββββββββ | 6/29 [00:17<00:45, 1.97s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 24%|ββββββββββββββββββββ | 7/29 [00:18<00:36, 1.66s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 28%|βββββββββββββββββββββββ | 8/29 [00:19<00:27, 1.29s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Sorry.. run again...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 31%|ββββββββββββββββββββββββββ | 9/29 [00:19<00:22, 1.12s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 34%|βββββββββββββββββββββββββββββ | 10/29 [00:20<00:18, 1.03it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 38%|βββββββββββββββββββββββββββββββ | 11/29 [00:21<00:18, 1.03s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 41%|ββββββββββββββββββββββββββββββββββ | 12/29 [00:22<00:14, 1.14it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 45%|βββββββββββββββββββββββββββββββββββββ | 13/29 [00:22<00:12, 1.27it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 48%|ββββββββββββββββββββββββββββββββββββββββ | 14/29 [00:23<00:13, 1.11it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 52%|βββββββββββββββββββββββββββββββββββββββββββ | 15/29 [00:24<00:12, 1.13it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 55%|ββββββββββββββββββββββββββββββββββββββββββββββ | 16/29 [00:25<00:11, 1.11it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 59%|ββββββββββββββββββββββββββββββββββββββββββββββββ | 17/29 [00:26<00:10, 1.18it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 62%|βββββββββββββββββββββββββββββββββββββββββββββββββββ | 18/29 [00:27<00:08, 1.28it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Sorry.. run again...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 66%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 19/29 [00:28<00:08, 1.18it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Sorry.. run again...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 20/29 [00:29<00:08, 1.05it/s]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 72%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 21/29 [00:31<00:09, 1.20s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 76%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 22/29 [00:32<00:08, 1.27s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 79%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 23/29 [00:33<00:07, 1.30s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 83%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 24/29 [00:35<00:06, 1.31s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 86%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 25/29 [00:37<00:06, 1.52s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 90%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 26/29 [00:38<00:04, 1.45s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 27/29 [00:39<00:02, 1.43s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- " 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 28/29 [00:41<00:01, 1.58s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- "100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 29/29 [00:42<00:00, 1.35s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r",
- "100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 29/29 [00:43<00:00, 1.50s/it]"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Sorry.. run again...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\n"
- ]
- }
- ],
- "source": [
- "df.loc[df['source']=='female','text'] =\\\n",
- "df.loc[df['source']=='female',:].progress_apply(lambda x : decodeSpeech(path_to_audio, x['start_time'], x['end_time'], language), axis=1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " source \n",
- " start_time \n",
- " end_time \n",
- " text \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " 2 \n",
- " female \n",
- " 6.88 \n",
- " 48.82 \n",
- " merci ma cousine \n",
- " \n",
- " \n",
- " 5 \n",
- " female \n",
- " 86.28 \n",
- " 108.46 \n",
- " du coup ton copain Γ§a fait une semaine amoureuse \n",
- " \n",
- " \n",
- " 8 \n",
- " female \n",
- " 118.48 \n",
- " 122.20 \n",
- " numΓ©ro inconnu \n",
- " \n",
- " \n",
- " 10 \n",
- " female \n",
- " 126.16 \n",
- " 127.84 \n",
- " ouais c'est moi c'est qui \n",
- " \n",
- " \n",
- " 12 \n",
- " female \n",
- " 129.82 \n",
- " 131.82 \n",
- " Ouais je crois je me souviens \n",
- " \n",
- " \n",
- " 14 \n",
- " female \n",
- " 133.90 \n",
- " 139.66 \n",
- " Γ§a va bien remis \n",
- " \n",
- " \n",
- " 16 \n",
- " female \n",
- " 149.46 \n",
- " 150.72 \n",
- " None \n",
- " \n",
- " \n",
- " 18 \n",
- " female \n",
- " 152.72 \n",
- " 157.26 \n",
- " du coup je crois que \n",
- " \n",
- " \n",
- " 21 \n",
- " female \n",
- " 159.34 \n",
- " 161.26 \n",
- " Alex enchantΓ© \n",
- " \n",
- " \n",
- " 23 \n",
- " female \n",
- " 162.86 \n",
- " 167.62 \n",
- " c'est que des trucs chez moi \n",
- " \n",
- " \n",
- " 26 \n",
- " female \n",
- " 168.94 \n",
- " 170.40 \n",
- " bah ouais je crois bien ouais \n",
- " \n",
- " \n",
- " 28 \n",
- " female \n",
- " 171.72 \n",
- " 174.12 \n",
- " c'est un peu galère avec ma mère \n",
- " \n",
- " \n",
- " 30 \n",
- " female \n",
- " 176.70 \n",
- " 180.60 \n",
- " ok cool vers oΓΉ \n",
- " \n",
- " \n",
- " 33 \n",
- " female \n",
- " 189.86 \n",
- " 191.40 \n",
- " 34 avenue Gambetta \n",
- " \n",
- " \n",
- " 37 \n",
- " female \n",
- " 200.00 \n",
- " 201.72 \n",
- " 36 V 45 \n",
- " \n",
- " \n",
- " 39 \n",
- " female \n",
- " 203.14 \n",
- " 204.68 \n",
- " mais je crois que j'ai dΓ©jΓ hΓ’te d'Γͺtre \n",
- " \n",
- " \n",
- " 41 \n",
- " female \n",
- " 206.30 \n",
- " 207.74 \n",
- " None \n",
- " \n",
- " \n",
- " 43 \n",
- " female \n",
- " 217.00 \n",
- " 218.44 \n",
- " None \n",
- " \n",
- " \n",
- " 45 \n",
- " female \n",
- " 222.84 \n",
- " 225.88 \n",
- " Ouais Γ demain bisous \n",
- " \n",
- " \n",
- " 47 \n",
- " female \n",
- " 228.96 \n",
- " 240.12 \n",
- " bah c'est bon j'envoie demain trop bien je t'a... \n",
- " \n",
- " \n",
- " 49 \n",
- " female \n",
- " 241.70 \n",
- " 246.42 \n",
- " et aller chez ouais en plus d'habitude j'aime ... \n",
- " \n",
- " \n",
- " 51 \n",
- " female \n",
- " 248.10 \n",
- " 254.48 \n",
- " et il t'a prise par derrière deux fois que la ... \n",
- " \n",
- " \n",
- " 53 \n",
- " female \n",
- " 256.04 \n",
- " 261.74 \n",
- " Il t'a pris Γ§a aussi on est allΓ© un peu fort j... \n",
- " \n",
- " \n",
- " 55 \n",
- " female \n",
- " 265.30 \n",
- " 275.96 \n",
- " du coup ton copain alors la photo j'en ai pas ... \n",
- " \n",
- " \n",
- " 57 \n",
- " female \n",
- " 289.16 \n",
- " 293.62 \n",
- " il s'appelle comment mon copain \n",
- " \n",
- " \n",
- " 59 \n",
- " female \n",
- " 294.62 \n",
- " 301.40 \n",
- " mettez en plus on a mΓͺme pas mΓͺme pas beaucoup... \n",
- " \n",
- " \n",
- " 61 \n",
- " female \n",
- " 304.66 \n",
- " 313.68 \n",
- " c'est fort c'est mΓͺme en fait c'Γ©tait juste le... \n",
- " \n",
- " \n",
- " 64 \n",
- " female \n",
- " 337.82 \n",
- " 340.70 \n",
- " non t'inquiète il vous connaissez \n",
- " \n",
- " \n",
- " 68 \n",
- " female \n",
- " 352.28 \n",
- " 353.10 \n",
- " None \n",
- " \n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " source start_time end_time \\\n",
- "2 female 6.88 48.82 \n",
- "5 female 86.28 108.46 \n",
- "8 female 118.48 122.20 \n",
- "10 female 126.16 127.84 \n",
- "12 female 129.82 131.82 \n",
- "14 female 133.90 139.66 \n",
- "16 female 149.46 150.72 \n",
- "18 female 152.72 157.26 \n",
- "21 female 159.34 161.26 \n",
- "23 female 162.86 167.62 \n",
- "26 female 168.94 170.40 \n",
- "28 female 171.72 174.12 \n",
- "30 female 176.70 180.60 \n",
- "33 female 189.86 191.40 \n",
- "37 female 200.00 201.72 \n",
- "39 female 203.14 204.68 \n",
- "41 female 206.30 207.74 \n",
- "43 female 217.00 218.44 \n",
- "45 female 222.84 225.88 \n",
- "47 female 228.96 240.12 \n",
- "49 female 241.70 246.42 \n",
- "51 female 248.10 254.48 \n",
- "53 female 256.04 261.74 \n",
- "55 female 265.30 275.96 \n",
- "57 female 289.16 293.62 \n",
- "59 female 294.62 301.40 \n",
- "61 female 304.66 313.68 \n",
- "64 female 337.82 340.70 \n",
- "68 female 352.28 353.10 \n",
- "\n",
- " text \n",
- "2 merci ma cousine \n",
- "5 du coup ton copain Γ§a fait une semaine amoureuse \n",
- "8 numΓ©ro inconnu \n",
- "10 ouais c'est moi c'est qui \n",
- "12 Ouais je crois je me souviens \n",
- "14 Γ§a va bien remis \n",
- "16 None \n",
- "18 du coup je crois que \n",
- "21 Alex enchantΓ© \n",
- "23 c'est que des trucs chez moi \n",
- "26 bah ouais je crois bien ouais \n",
- "28 c'est un peu galère avec ma mère \n",
- "30 ok cool vers oΓΉ \n",
- "33 34 avenue Gambetta \n",
- "37 36 V 45 \n",
- "39 mais je crois que j'ai dΓ©jΓ hΓ’te d'Γͺtre \n",
- "41 None \n",
- "43 None \n",
- "45 Ouais Γ demain bisous \n",
- "47 bah c'est bon j'envoie demain trop bien je t'a... \n",
- "49 et aller chez ouais en plus d'habitude j'aime ... \n",
- "51 et il t'a prise par derrière deux fois que la ... \n",
- "53 Il t'a pris Γ§a aussi on est allΓ© un peu fort j... \n",
- "55 du coup ton copain alors la photo j'en ai pas ... \n",
- "57 il s'appelle comment mon copain \n",
- "59 mettez en plus on a mΓͺme pas mΓͺme pas beaucoup... \n",
- "61 c'est fort c'est mΓͺme en fait c'Γ©tait juste le... \n",
- "64 non t'inquiète il vous connaissez \n",
- "68 None "
- ]
- },
- "execution_count": 39,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.loc[df['source']=='female',:]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {},
- "outputs": [],
- "source": [
- "from pydub import AudioSegment\n",
- "t1 = 168.94 * 1000 #Works in milliseconds\n",
- "t2 = 170.40 * 1000\n",
- "newAudio = AudioSegment.from_wav(path_to_audio)\n",
- "newAudio = newAudio[t1:t2]\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "pydub.audio_segment.AudioSegment"
- ]
- },
- "execution_count": 41,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "type(newAudio)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 43,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<_io.BufferedRandom name='C:\\\\Users\\\\mehdi\\\\Desktop\\\\data_for_good\\\\mm2_bechdelai-vision\\\\data\\\\sample_videos\\\\tests.wav'>"
- ]
- },
- "execution_count": 43,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "newAudio.export(os.path.abspath(os.path.join(path_to_audio, os.pardir, 'tests.wav')), format=\"wav\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "'bah ouais je crois bien ouais'"
- ]
- },
- "execution_count": 45,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "\n",
- "decodeSpeech(os.path.abspath(os.path.join(path_to_audio, os.pardir, 'tests.wav')), start_time = None, end_time = None, language = language)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {},
- "outputs": [],
- "source": [
- "#Resemblyzer"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.3"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/audio/bechdel_audio.ipynb b/notebooks/audio/bechdel_audio.ipynb
deleted file mode 100644
index f4149f6..0000000
--- a/notebooks/audio/bechdel_audio.ipynb
+++ /dev/null
@@ -1,2398 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "executionInfo": {
- "elapsed": 22176,
- "status": "ok",
- "timestamp": 1643749891148,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "PoueSBaJ2tOw",
- "outputId": "536f770c-216d-4ddb-ed1d-0f5daf705f71"
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Mounted at /content/drive\n"
- ]
- }
- ],
- "source": [
- "from google.colab import drive\n",
- "import os\n",
- "drive.mount('/content/drive')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "bKg4OIsQ2xdN"
- },
- "outputs": [],
- "source": [
- "!pip install transformers\n",
- "!pip install speechbrain\n",
- "!pip install inaSpeechSegmenter\n",
- "!pip install asrecognition\n",
- "!pip install SpeechRecognition\n",
- "!pip install pydub\n",
- "!pip install pyyaml==5.4.1"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "executionInfo": {
- "elapsed": 26,
- "status": "ok",
- "timestamp": 1643749945788,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "gZ7fGZkQ3CzG"
- },
- "outputs": [],
- "source": [
- "video_dir = '/content/drive/MyDrive/DataForGood/bechdel/data/video'\n",
- "audio_dir = '/content/drive/MyDrive/DataForGood/bechdel/data/audio'\n",
- "chunks = '/content/drive/MyDrive/DataForGood/bechdel/data/audio/chunks'\n",
- "folders = [video_dir, audio_dir, chunks]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "executionInfo": {
- "elapsed": 854,
- "status": "ok",
- "timestamp": 1643749946621,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "E0CZPdrJ3Dhl"
- },
- "outputs": [],
- "source": [
- "for folder in folders:\n",
- " if not os.path.isdir(folder) : \n",
- " !mkdir -p {folder}"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!wget https://github.com/dataforgoodfr/mm2_bechdelai-vision/blob/main/data/sample_audios/LA_LETTRE.wav -P {audio_dir}"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "executionInfo": {
- "elapsed": 211,
- "status": "ok",
- "timestamp": 1643750013245,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "LngMKj-93EIV"
- },
- "outputs": [],
- "source": [
- "audio_path = os.path.join(audio_dir, 'LA_LETTRE.wav')\n",
- "small_test = os.path.join(audio_dir, 'Enregistrement.wav')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "executionInfo": {
- "elapsed": 11056,
- "status": "ok",
- "timestamp": 1643750027879,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "pOnmpB5d3vLu"
- },
- "outputs": [],
- "source": [
- "import plotly.express as px\n",
- "import datetime\n",
- "import torch\n",
- "from torchaudio.sox_effects import apply_effects_file\n",
- "from transformers import AutoFeatureExtractor, AutoModelForAudioXVector\n",
- "from speechbrain.pretrained import SepformerSeparation as separator\n",
- "import torchaudio\n",
- "from speechbrain.pretrained import EncoderASR\n",
- "from asrecognition import ASREngine\n",
- "from pydub import AudioSegment\n",
- "import transformers\n",
- "import speech_recognition as sr\n",
- "from inaSpeechSegmenter import Segmenter\n",
- "from inaSpeechSegmenter.export_funcs import seg2csv, seg2textgrid\n",
- "import os\n",
- "import pandas as pd\n",
- "from tqdm import tqdm\n",
- "import re\n",
- "tqdm.pandas()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "executionInfo": {
- "elapsed": 326,
- "status": "ok",
- "timestamp": 1643750028190,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "z_XxbufZ4UIB"
- },
- "outputs": [],
- "source": [
- "def similarity_fn(path1, path2,treshold): \n",
- " wav1, _ = apply_effects_file(path1, EFFECTS)\n",
- " wav2, _ = apply_effects_file(path2, EFFECTS)\n",
- " \n",
- "\n",
- " input1 = feature_extractor(wav1.squeeze(0), return_tensors=\"pt\", sampling_rate=16000).input_values.to(device)\n",
- " input2 = feature_extractor(wav2.squeeze(0), return_tensors=\"pt\", sampling_rate=16000).input_values.to(device)\n",
- "\n",
- " with torch.no_grad():\n",
- " emb1 = model(input1).embeddings\n",
- " emb2 = model(input2).embeddings\n",
- " emb1 = torch.nn.functional.normalize(emb1, dim=-1).cpu()\n",
- " emb2 = torch.nn.functional.normalize(emb2, dim=-1).cpu()\n",
- " similarity = cosine_sim(emb1, emb2).numpy()[0]\n",
- "\n",
- " if similarity >= treshold:\n",
- " output = True\n",
- " else:\n",
- " output = False\n",
- "\n",
- " return output\n",
- "\n",
- "\n",
- "def speech_segmenter(segmenter, wavfile): \n",
- " segmentation = segmenter(wavfile)\n",
- " \n",
- " mapper = {'source' : [], 'start_time' : [] , 'end_time' : [] }\n",
- " \n",
- " for seg in segmentation:\n",
- " mapper['source'].append(seg[0])\n",
- " mapper['start_time'].append(seg[1])\n",
- " mapper['end_time'].append(seg[2])\n",
- "\n",
- "\n",
- " df = pd.DataFrame(mapper)\n",
- " \n",
- " return df\n",
- "\n",
- "def map_numbers(x,mapper):\n",
- " for k in mapper.keys():\n",
- " if x in mapper[k]:\n",
- " return k\n",
- "\n",
- "\n",
- "\n",
- "def crop_and_save_segments(wavfile, chunks_path, index, start_time, end_time):\n",
- " sound = AudioSegment.from_file(wavfile)\n",
- " segment = sound[start_time*1000:end_time*1000]\n",
- " segment.export(os.path.join(chunks_path,f'female{index}.wav'), format=\"wav\")\n",
- " segment_fname = os.path.join(chunks_path,f'female{index}.wav')\n",
- " return segment_fname\n",
- " \n",
- "def indexing_persons(path1, path2, treshold, women_index):\n",
- " is_same = similarity_fn(path1, path2, treshold)\n",
- " return women_index if is_same else -1 \n",
- "\n",
- "\n",
- "def compare_voices_from_audio(wavfile, chunks_path, model, segmenter, treshold ) :\n",
- " \"\"\"\n",
- " This function processes a wavefile and crops it according to female segmented speeches\n",
- " It then takes saved chunks of female voices and compares them one-to-one in a O(n) way\n",
- " It adds a categorical column indexing each woman in the audio\n",
- " It then returns : \n",
- " the segmentation dataframe\n",
- " the distinct women dataframe\n",
- " the indexed persons dataframe\n",
- "\n",
- " \"\"\"\n",
- " print(r'******************')\n",
- " print(\"Segmenting audio file...\")\n",
- " print(r'******************')\n",
- " df = speech_segmenter(segmenter, wavfile)\n",
- " df.reset_index(drop=False,inplace=True)\n",
- " \n",
- " print(r'******************')\n",
- " print(\"Exporting cropped audio files...\")\n",
- " print(r'******************')\n",
- " df.loc[df['source']=='female',\"female_fname\"] = df.loc[df['source']=='female',:].progress_apply(lambda x :\\\n",
- " crop_and_save_segments(wavfile, chunks_path, x['index'], x['start_time'], x['end_time']), axis=1)\n",
- "\n",
- " df['person_indexer'] = -1\n",
- " all_women = df.loc[df['source']=='female',:]\n",
- " \n",
- " \n",
- " print(r'******************')\n",
- " print(\"Comparing Voices...\")\n",
- " print(r'******************')\n",
- " all_women.reset_index(drop=True,inplace=True)\n",
- " grappes = []\n",
- " dropped = []\n",
- " for i in tqdm(range(1,len(all_women))):\n",
- " to_loop = list(range(0,i))\n",
- " for x in dropped:\n",
- " to_loop.remove(x)\n",
- " for j in to_loop[::-1]:\n",
- " rowi1 = all_women.loc[j,\"female_fname\"]\n",
- " rowi = all_women.loc[i,\"female_fname\"]\n",
- " is_same = similarity_fn(os.path.join(chunks_path,rowi1), os.path.join(chunks_path,rowi),treshold=treshold)\n",
- " if is_same :\n",
- " grappes.append([rowi,rowi1])\n",
- " dropped.append(j)\n",
- " break \n",
- " \n",
- " \n",
- " print(r'******************')\n",
- " print(\"Indexing Persons...\")\n",
- " print(r'******************')\n",
- " for cpl in grappes:\n",
- " cpl[0] = int(re.findall(r'\\d+', cpl[0])[0])\n",
- " cpl[1] = int(re.findall(r'\\d+', cpl[1])[0])\n",
- "\n",
- " groups = []\n",
- " while len(grappes)!=0: \n",
- " group = []\n",
- " to_drop = []\n",
- " for i in tqdm(range(len(grappes))):\n",
- " if i==0:\n",
- " group = list(set(group + grappes[i]))\n",
- " if len(set(group + grappes[i])) < len(group + grappes[i]):\n",
- " group = list(set(group + grappes[i]))\n",
- " to_drop.append(i)\n",
- "\n",
- " groups.append(group)\n",
- " to_keep = list(set(list(range(len(grappes)))) - set(to_drop))\n",
- " grappes = [grappes[p] for p in to_keep]\n",
- " \n",
- " mapper = {k : groups[k] for k in range(len(groups))}\n",
- "\n",
- " all_women['number'] = all_women['female_fname'].progress_apply(lambda x : int(re.findall(r'\\d+', x)[0]))\n",
- "\n",
- " all_women['person_indexer'] = all_women['number'].progress_apply(lambda x : map_numbers(x,mapper))\n",
- "\n",
- " return df, all_women , groups, dropped"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "executionInfo": {
- "elapsed": 212,
- "status": "ok",
- "timestamp": 1643750029651,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
- },
- "user_tz": -60
- },
- "id": "bmY1y21L49ly"
- },
- "outputs": [],
- "source": [
- "treshold = 0.80\n",
- "EFFECTS = [\n",
- " [\"remix\", \"-\"],\n",
- " [\"channels\", \"1\"],\n",
- " [\"rate\", \"16000\"],\n",
- " [\"gain\", \"-1.0\"],\n",
- " [\"silence\", \"1\", \"0.1\", \"0.1%\", \"-1\", \"0.1\", \"0.1%\"],\n",
- " [\"trim\", \"0\", \"10\"],\n",
- "]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 113,
- "referenced_widgets": [
- "c74dc430d42b4da3bf609c8eea8f62a5",
- "1edc0fa8263249a2beeb9598b94ca4eb",
- "17f5c6dc32a849e89d6412116d6b421f",
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- "seg = Segmenter()\n",
- "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
- "model_name = \"microsoft/wavlm-base-plus-sv\"\n",
- "feature_extractor = AutoFeatureExtractor.from_pretrained(model_name)\n",
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- "cosine_sim = torch.nn.CosineSimilarity(dim=-1)"
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- "text": [
- "******************\n",
- "Segmenting audio file...\n",
- "******************\n"
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- "/usr/local/lib/python3.7/dist-packages/pyannote/algorithms/utils/viterbi.py:88: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
- " for e, c in six.moves.zip(emission.T, consecutive)\n",
- "/usr/local/lib/python3.7/dist-packages/pyannote/algorithms/utils/viterbi.py:97: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
- " for e, c in six.moves.zip(constraint.T, consecutive)\n",
- "/usr/local/lib/python3.7/dist-packages/inaSpeechSegmenter/segmenter.py:60: RuntimeWarning: invalid value encountered in subtract\n",
- " data = (data - np.mean(data, axis=1).reshape((len(data), 1))) / np.std(data, axis=1).reshape((len(data), 1))\n",
- "/usr/local/lib/python3.7/dist-packages/numpy/core/_methods.py:202: RuntimeWarning: invalid value encountered in subtract\n",
- " x = asanyarray(arr - arrmean)\n"
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- "name": "stdout",
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- "text": [
- "******************\n",
- "Exporting cropped audio files...\n",
- "******************\n"
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- "output_type": "stream",
- "text": [
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- ]
- },
- {
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- "output_type": "stream",
- "text": [
- "******************\n",
- "Comparing Voices...\n",
- "******************\n"
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- "text": [
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- "text": [
- "******************\n",
- "Indexing Persons...\n",
- "******************\n"
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- "output_type": "stream",
- "text": [
- "100%|ββββββββββ| 14/14 [00:00<00:00, 72137.91it/s]\n",
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- "A value is trying to be set on a copy of a slice from a DataFrame.\n",
- "Try using .loc[row_indexer,col_indexer] = value instead\n",
- "\n",
- "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
- "100%|ββββββββββ| 17/17 [00:00<00:00, 23863.18it/s]\n",
- "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:130: SettingWithCopyWarning: \n",
- "A value is trying to be set on a copy of a slice from a DataFrame.\n",
- "Try using .loc[row_indexer,col_indexer] = value instead\n",
- "\n",
- "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
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- ]
- },
- {
- "cell_type": "code",
- "execution_count": 53,
- "metadata": {
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- "status": "ok",
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- "user": {
- "displayName": "Mehdi Agunaou",
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- "df = df.drop(columns=['person_indexer'])"
- ]
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- {
- "cell_type": "code",
- "execution_count": 54,
- "metadata": {
- "executionInfo": {
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- "user": {
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- "id": "OVNUZFyNRBvl"
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- "source": [
- "all_women2 = all_women[['female_fname','person_indexer']]"
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- },
- {
- "cell_type": "code",
- "execution_count": 92,
- "metadata": {
- "executionInfo": {
- "elapsed": 251,
- "status": "ok",
- "timestamp": 1643755468504,
- "user": {
- "displayName": "Mehdi Agunaou",
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- "userId": "15746146104404176496"
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- "source": [
- "df_graph = pd.merge(df, all_women2 , 'left' , on='female_fname')"
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- {
- "cell_type": "code",
- "execution_count": 93,
- "metadata": {
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- "timestamp": 1643755469637,
- "user": {
- "displayName": "Mehdi Agunaou",
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- "userId": "15746146104404176496"
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- "df_graph.drop(columns=['index'],inplace=True)"
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- {
- "cell_type": "code",
- "execution_count": 94,
- "metadata": {
- "executionInfo": {
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- "status": "ok",
- "timestamp": 1643755475295,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
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- "id": "lbQA-QjPRpv0"
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- "outputs": [],
- "source": [
- "df_graph['start_datetime'] = df_graph['start_time'].apply(lambda x : datetime.datetime.now() + datetime.timedelta(seconds=x))\n",
- "df_graph['end_datetime'] = df_graph['end_time'].apply(lambda x : datetime.datetime.now() + datetime.timedelta(seconds=x))"
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- {
- "cell_type": "code",
- "execution_count": 95,
- "metadata": {
- "executionInfo": {
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- "status": "ok",
- "timestamp": 1643755480268,
- "user": {
- "displayName": "Mehdi Agunaou",
- "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s64",
- "userId": "15746146104404176496"
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- "id": "L6C76IlvRxxa"
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- "outputs": [],
- "source": [
- "df_graph['person_indexer'] = df_graph['person_indexer'].fillna(-1).astype('int').astype('object')"
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- "df_graph.loc[df_graph['source']== 'noise' ,'person_indexer'] = 'bruit'\n",
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- "musique 13\n",
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diff --git a/notebooks/audio/gender_and_text_recognition.ipynb b/notebooks/audio/gender_and_text_recognition.ipynb
deleted file mode 100644
index ac12292..0000000
--- a/notebooks/audio/gender_and_text_recognition.ipynb
+++ /dev/null
@@ -1,602 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "duJI03wcaVcH"
- },
- "source": [
- "# Installation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "DvVVFP7Bdkbw"
- },
- "outputs": [],
- "source": [
- "# moviepy [MIT Licence] >>> extraction de son\n",
- "# https://towardsdatascience.com/extracting-audio-from-video-using-python-58856a940fd\n",
- "\n",
- "# inaSpeechSegmenter [MIT Licence] >>> reconnaissance du genre du locuteur\n",
- "\n",
- "# SpeechRecognition [BSD License] >>> speech to text\n",
- "# https://pypi.org/project/SpeechRecognition/2.1.3/\n",
- "# https://openclassrooms.com/forum/sujet/reconnaissance-vocale-en-python-1\n",
- "# https://medium.com/@garcjes/transcribe-a-podcast-in-python-with-vosk-api-35eba7d96c1f"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "aIue2grbaRt7",
- "outputId": "23c1c72d-8354-4eae-83d4-690d1bac4137"
- },
- "outputs": [],
- "source": [
- "# !pip install moviepy\n",
- "# !pip install inaSpeechSegmenter\n",
- "# !pip install SpeechRecognition"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "zD4yPXOCf1Re"
- },
- "source": [
- "# 1. Extract the audio with moviepy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "-wX2uuk3ZfFC",
- "outputId": "29ba04cb-a622-4a45-d833-3965cf2bbdca"
- },
- "outputs": [],
- "source": [
- "import moviepy.editor as mp"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "id": "jtac8ZyEbH6K"
- },
- "outputs": [],
- "source": [
- "# Make sure to upload a video in \"./media\" !\n",
- "path_to_the_video = r\"./media/video2.mp4\"\n",
- "my_clip = mp.VideoFileClip(path_to_the_video)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "d2DcL6D7fPTp",
- "outputId": "495d4447-31c6-471a-90cf-a9b6bed028ce"
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "MoviePy - Writing audio in ./media/extract.wav\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- " "
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "MoviePy - Done.\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\r"
- ]
- }
- ],
- "source": [
- "# Extract the audio\n",
- "my_clip.audio.write_audiofile(r\"./media/extract.wav\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "SqVCNh-ugD3I"
- },
- "source": [
- "# 2. Extract the text with SpeechRecognition"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "id": "AupEsTpgdfYD"
- },
- "outputs": [],
- "source": [
- "import speech_recognition as sr"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "id": "nCk5PadigHjg"
- },
- "outputs": [],
- "source": [
- "def decodeSpeech(wavefile, start_time = None, end_time = None, language = None):\n",
- " \n",
- " r = sr.Recognizer()\n",
- " #r.pause_threshold = 3\n",
- " #r.dynamic_energy_adjustment_damping = 0.5\n",
- "\n",
- " with sr.WavFile(wavefile) as source:\n",
- " if start_time == None and end_time == None:\n",
- " audio_text = r.record(source)\n",
- " else:\n",
- " audio_text = r.record(source, duration = end_time - start_time, offset = start_time)\n",
- " \n",
- " if language == None: #default language is American English\n",
- " lg = \"en-US\"\n",
- " else:\n",
- " lg = language\n",
- "\n",
- " # recoginize_() method will throw a request error if the API is unreachable, hence using exception handling\n",
- " try:\n",
- " \n",
- " # using google speech recognition\n",
- " text = r.recognize_google(audio_text, language = lg)\n",
- " print('Converting audio transcripts into text ...')\n",
- " return text\n",
- " \n",
- " except:\n",
- " print('Sorry.. run again...')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "id": "nd7qZeb4gqyF"
- },
- "outputs": [],
- "source": [
- "# Define the audio file to perform speech-recognition and segmentation:\n",
- "WAVFILE = \"./media/extract.wav\"\n",
- "language = \"fr-FR\""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "bS5u0SuRhpg9"
- },
- "source": [
- "# 3. Gender Recognition with inaSpeechSegmenter"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {
- "id": "8uLPzHnEgwqb"
- },
- "outputs": [],
- "source": [
- "# Load the API\n",
- "from inaSpeechSegmenter import Segmenter\n",
- "from inaSpeechSegmenter.export_funcs import seg2csv, seg2textgrid"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "id": "INydwLYlh6i9"
- },
- "outputs": [],
- "source": [
- "# select a media to analyse\n",
- "# any media supported by ffmpeg may be used (video, audio, urls)\n",
- "media = WAVFILE"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "id": "wUTbj7adh_hA"
- },
- "outputs": [],
- "source": [
- "# create an instance of speech segmenter\n",
- "# this loads neural networks and may last few seconds\n",
- "# Warnings have no incidence on the results\n",
- "seg = Segmenter()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {
- "id": "6yPE4gT4iBIo"
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "2021-12-22 08:53:26.432257: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n"
- ]
- }
- ],
- "source": [
- "# segmentation is performed using the __call__ method of the segmenter instance\n",
- "segmentation = seg(media)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "lpbvC5X4iCer",
- "outputId": "4a322823-17b1-432f-be22-b7e24683d86f"
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[('male', 0.0, 3.24), ('female', 3.24, 4.28), ('noise', 4.28, 6.72), ('male', 6.72, 15.22), ('female', 15.22, 16.46), ('noEnergy', 16.46, 17.18), ('male', 17.18, 20.18), ('noise', 20.18, 24.16), ('male', 24.16, 29.1), ('female', 29.1, 31.46), ('male', 31.46, 34.46), ('noEnergy', 34.46, 35.46), ('female', 35.46, 43.52)]\n"
- ]
- }
- ],
- "source": [
- "# the result is a list of tuples\n",
- "# each tuple contains:\n",
- "# * label in 'male', 'female', 'music', 'noEnergy'\n",
- "# * start time of the segment\n",
- "# * end time of the segment\n",
- "print(segmentation)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "gItfxBigiloO",
- "outputId": "89978f50-fac8-4c34-9806-6b6ae8a51d4d"
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Converting audio transcripts into text ...\n",
- "Converting audio transcripts into text ...\n",
- "Sorry.. run again...\n",
- "Converting audio transcripts into text ...\n",
- "Sorry.. run again...\n",
- "Sorry.. run again...\n",
- "Converting audio transcripts into text ...\n",
- "Sorry.. run again...\n",
- "Converting audio transcripts into text ...\n",
- "Converting audio transcripts into text ...\n",
- "Converting audio transcripts into text ...\n",
- "Sorry.. run again...\n",
- "Converting audio transcripts into text ...\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[{'type': 'male', 'start_time': 0.0, 'end_time': 3.24, 'text': 'et alors'},\n",
- " {'type': 'female',\n",
- " 'start_time': 3.24,\n",
- " 'end_time': 4.28,\n",
- " 'text': 'donne-moi mon'},\n",
- " {'type': 'noise', 'start_time': 4.28, 'end_time': 6.72, 'text': None},\n",
- " {'type': 'male',\n",
- " 'start_time': 6.72,\n",
- " 'end_time': 15.22,\n",
- " 'text': \"tu as fait quelque chose pour mΓ©riter ta nourriture ses cΓ©rΓ©ales je sais payer avec mon argent j'ai gagnΓ© parce que j'ai travaillΓ©\"},\n",
- " {'type': 'female', 'start_time': 15.22, 'end_time': 16.46, 'text': None},\n",
- " {'type': 'noEnergy', 'start_time': 16.46, 'end_time': 17.18, 'text': None},\n",
- " {'type': 'male',\n",
- " 'start_time': 17.18,\n",
- " 'end_time': 20.18,\n",
- " 'text': \"j'ai dΓ©jΓ vu dans des dans le quartier\"},\n",
- " {'type': 'noise', 'start_time': 20.18, 'end_time': 24.16, 'text': None},\n",
- " {'type': 'male',\n",
- " 'start_time': 24.16,\n",
- " 'end_time': 29.1,\n",
- " 'text': 'choisis entre 1 et 6 tu es une voleuse tant pis pour toi'},\n",
- " {'type': 'female',\n",
- " 'start_time': 29.1,\n",
- " 'end_time': 31.46,\n",
- " 'text': \"qu'est-ce que vous croyez qu'on choisit d'Γͺtre Γ la rue\"},\n",
- " {'type': 'male',\n",
- " 'start_time': 31.46,\n",
- " 'end_time': 34.46,\n",
- " 'text': 'tu es jeune si tu voulais vraiment bosser tu bosses'},\n",
- " {'type': 'noEnergy', 'start_time': 34.46, 'end_time': 35.46, 'text': None},\n",
- " {'type': 'female',\n",
- " 'start_time': 35.46,\n",
- " 'end_time': 43.52,\n",
- " 'text': \"ma mère était toxico ma grand-mère qui m'a élevé elle a bossé toute sa vie comme caissière pour m'aider à payer mes études\"}]"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Perform speech-to-text with SpeechRecognition for each element in the male/female segmentation\n",
- "\n",
- "segmentation_bis = []\n",
- "\n",
- "for segment in segmentation:\n",
- " segment_bis = {\"type\" : segment[0],\n",
- " \"start_time\" : segment[1],\n",
- " \"end_time\" : segment[2],\n",
- " \"text\" : decodeSpeech(wavefile = WAVFILE, start_time = segment[1], end_time = segment[2], language = language)\n",
- " }\n",
- " segmentation_bis.append(segment_bis)\n",
- "\n",
- "segmentation_bis"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 332
- },
- "id": "OYd7cPvwiK9_",
- "outputId": "b60a5b9c-6214-4fba-8b08-cf41f7245b1a"
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " type \n",
- " start_time \n",
- " end_time \n",
- " text \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " 0 \n",
- " male \n",
- " 0.00 \n",
- " 3.24 \n",
- " et alors \n",
- " \n",
- " \n",
- " 1 \n",
- " female \n",
- " 3.24 \n",
- " 4.28 \n",
- " donne-moi mon \n",
- " \n",
- " \n",
- " 3 \n",
- " male \n",
- " 6.72 \n",
- " 15.22 \n",
- " tu as fait quelque chose pour mΓ©riter ta nourr... \n",
- " \n",
- " \n",
- " 4 \n",
- " female \n",
- " 15.22 \n",
- " 16.46 \n",
- " None \n",
- " \n",
- " \n",
- " 6 \n",
- " male \n",
- " 17.18 \n",
- " 20.18 \n",
- " j'ai dΓ©jΓ vu dans des dans le quartier \n",
- " \n",
- " \n",
- " 8 \n",
- " male \n",
- " 24.16 \n",
- " 29.10 \n",
- " choisis entre 1 et 6 tu es une voleuse tant pi... \n",
- " \n",
- " \n",
- " 9 \n",
- " female \n",
- " 29.10 \n",
- " 31.46 \n",
- " qu'est-ce que vous croyez qu'on choisit d'Γͺtre... \n",
- " \n",
- " \n",
- " 10 \n",
- " male \n",
- " 31.46 \n",
- " 34.46 \n",
- " tu es jeune si tu voulais vraiment bosser tu b... \n",
- " \n",
- " \n",
- " 12 \n",
- " female \n",
- " 35.46 \n",
- " 43.52 \n",
- " ma mère était toxico ma grand-mère qui m'a éle... \n",
- " \n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " type start_time end_time \\\n",
- "0 male 0.00 3.24 \n",
- "1 female 3.24 4.28 \n",
- "3 male 6.72 15.22 \n",
- "4 female 15.22 16.46 \n",
- "6 male 17.18 20.18 \n",
- "8 male 24.16 29.10 \n",
- "9 female 29.10 31.46 \n",
- "10 male 31.46 34.46 \n",
- "12 female 35.46 43.52 \n",
- "\n",
- " text \n",
- "0 et alors \n",
- "1 donne-moi mon \n",
- "3 tu as fait quelque chose pour mΓ©riter ta nourr... \n",
- "4 None \n",
- "6 j'ai dΓ©jΓ vu dans des dans le quartier \n",
- "8 choisis entre 1 et 6 tu es une voleuse tant pi... \n",
- "9 qu'est-ce que vous croyez qu'on choisit d'Γͺtre... \n",
- "10 tu es jeune si tu voulais vraiment bosser tu b... \n",
- "12 ma mère était toxico ma grand-mère qui m'a éle... "
- ]
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "import pandas as pd\n",
- "df = pd.DataFrame(segmentation_bis)\n",
- "df[(df[\"type\"] == \"male\") | (df[\"type\"] == \"female\")]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "GFvpq8ecjck8"
- },
- "source": [
- "# IdΓ©es pour la suite"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "SythQ02YjehZ"
- },
- "outputs": [],
- "source": [
- "# DΓ©tection de voix distinctes --> du type --> female1, female2, male1, etc.\n",
- "# ---> resemblyzer ?\n",
- "# ---> https://www.audiolabs-erlangen.de/resources/2017-CountNet"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "Ik2DmGa04M_d"
- },
- "outputs": [],
- "source": [
- "# !pip install resemblyze\n",
- "\n",
- "# from resemblyzer import VoiceEncoder, preprocess_wav\n",
- "# from pathlib import Path\n",
- "# import numpy as np\n",
- "\n",
- "# WAVFILE = '/content/extraction_du_son.wav'\n",
- "\n",
- "# fpath = Path(WAVFILE)\n",
- "# wav = preprocess_wav(fpath)\n",
- "\n",
- "# encoder = VoiceEncoder()\n",
- "# embed = encoder.embed_utterance(wav)\n",
- "# np.set_printoptions(precision=3, suppress=True)\n",
- "# # print(embed)"
- ]
- }
- ],
- "metadata": {
- "colab": {
- "collapsed_sections": [],
- "name": "21-12-09 - Extraction du genre et du texte.ipynb",
- "provenance": []
- },
- "kernelspec": {
- "display_name": "Python 3",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.3"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
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index ec4d928..df35288 100644
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name = "anyio"
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optional = false
python-versions = ">=3.6.2"
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category = "main"
optional = false
python-versions = "*"
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optional = false
python-versions = "*"
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category = "main"
optional = false
python-versions = ">=3.6"
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tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"]
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category = "main"
optional = false
python-versions = ">=3.6"
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name = "ftfy"
@@ -439,10 +1224,25 @@ description = "Fixes mojibake and other problems with Unicode, after the fact"
category = "main"
optional = false
python-versions = ">=3.7,<4"
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@@ -450,14 +1250,22 @@ description = "Python AST that abstracts the underlying Python version"
category = "main"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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python-versions = "*"
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@@ -473,42 +1281,58 @@ description = "Copy your docs directly to the gh-pages branch."
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optional = false
python-versions = "*"
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category = "main"
optional = false
python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
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six = ">=1.9.0"
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category = "main"
optional = false
python-versions = ">=3.6"
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optional = false
python-versions = "*"
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category = "main"
optional = false
python-versions = ">=3.7"
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+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
[[package]]
name = "importlib-resources"
-version = "5.10.0"
+version = "5.12.0"
description = "Read resources from Python packages"
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
+ {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
+ {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
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zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
[package.extras]
-docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "furo", "jaraco.tidelift (>=1.4)"]
-testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)"]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
+[[package]]
+name = "inaspeechsegmenter"
+version = "0.7.6"
+description = "CNN-based audio segmentation toolkit. Does voice activity detection, speech detection, music detection, noise detection, speaker gender recognition."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+ {file = "inaSpeechSegmenter-0.7.6-py3-none-any.whl", hash = "sha256:c712d11e17e75f2c7f4f6a24448a639da861a0361561c467f144194afb2b252b"},
+ {file = "inaSpeechSegmenter-0.7.6.tar.gz", hash = "sha256:6c888a613b4588fcda4958f5131da2a17af18e319cb9023a6ecfbd2433ba5be2"},
+]
+
+[package.dependencies]
+matplotlib = "*"
+numpy = "*"
+pandas = "*"
+"pyannote.algorithms" = "*"
+"pyannote.core" = "*"
+"pyannote.parser" = "*"
+Pyro4 = "*"
+pytextgrid = "*"
+scikit-image = "*"
+soundfile = "*"
+tensorflow = "*"
[[package]]
name = "ipykernel"
-version = "6.16.1"
+version = "6.21.2"
description = "IPython Kernel for Jupyter"
category = "main"
optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+ {file = "ipykernel-6.21.2-py3-none-any.whl", hash = "sha256:430d00549b6aaf49bd0f5393150691edb1815afa62d457ee6b1a66b25cb17874"},
+ {file = "ipykernel-6.21.2.tar.gz", hash = "sha256:6e9213484e4ce1fb14267ee435e18f23cc3a0634e635b9fb4ed4677b84e0fdf8"},
+]
[package.dependencies]
appnope = {version = "*", markers = "platform_system == \"Darwin\""}
-debugpy = ">=1.0"
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
ipython = ">=7.23.1"
jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
matplotlib-inline = ">=0.1"
nest-asyncio = "*"
packaging = "*"
psutil = "*"
-pyzmq = ">=17"
+pyzmq = ">=20"
tornado = ">=6.1"
-traitlets = ">=5.1.0"
+traitlets = ">=5.4.0"
[package.extras]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-alt"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest-cov", "pytest-timeout", "pytest (>=7.0)"]
+cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
[[package]]
name = "ipython"
-version = "8.5.0"
+version = "8.10.0"
description = "IPython: Productive Interactive Computing"
category = "main"
optional = false
python-versions = ">=3.8"
+files = [
+ {file = "ipython-8.10.0-py3-none-any.whl", hash = "sha256:b38c31e8fc7eff642fc7c597061fff462537cf2314e3225a19c906b7b0d8a345"},
+ {file = "ipython-8.10.0.tar.gz", hash = "sha256:b13a1d6c1f5818bd388db53b7107d17454129a70de2b87481d555daede5eb49e"},
+]
[package.dependencies]
appnope = {version = "*", markers = "sys_platform == \"darwin\""}
@@ -680,15 +1786,15 @@ jedi = ">=0.16"
matplotlib-inline = "*"
pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
pickleshare = "*"
-prompt-toolkit = ">3.0.1,<3.1.0"
+prompt-toolkit = ">=3.0.30,<3.1.0"
pygments = ">=2.4.0"
stack-data = "*"
traitlets = ">=5"
[package.extras]
-all = ["black", "Sphinx (>=1.3)", "ipykernel", "nbconvert", "nbformat", "ipywidgets", "notebook", "ipyparallel", "qtconsole", "pytest (<7.1)", "pytest-asyncio", "testpath", "curio", "matplotlib (!=3.2.0)", "numpy (>=1.19)", "pandas", "trio"]
+all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
black = ["black"]
-doc = ["Sphinx (>=1.3)"]
+doc = ["docrepr", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
kernel = ["ipykernel"]
nbconvert = ["nbconvert"]
nbformat = ["nbformat"]
@@ -696,7 +1802,7 @@ notebook = ["ipywidgets", "notebook"]
parallel = ["ipyparallel"]
qtconsole = ["qtconsole"]
test = ["pytest (<7.1)", "pytest-asyncio", "testpath"]
-test_extra = ["pytest (<7.1)", "pytest-asyncio", "testpath", "curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.19)", "pandas", "trio"]
+test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"]
[[package]]
name = "ipython-genutils"
@@ -705,14 +1811,22 @@ description = "Vestigial utilities from IPython"
category = "main"
optional = false
python-versions = "*"
+files = [
+ {file = "ipython_genutils-0.2.0-py2.py3-none-any.whl", hash = "sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8"},
+ {file = "ipython_genutils-0.2.0.tar.gz", hash = "sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8"},
+]
[[package]]
name = "ipywidgets"
-version = "8.0.2"
+version = "8.0.4"
description = "Jupyter interactive widgets"
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
+ {file = "ipywidgets-8.0.4-py3-none-any.whl", hash = "sha256:ebb195e743b16c3947fe8827190fb87b4d00979c0fbf685afe4d2c4927059fa1"},
+ {file = "ipywidgets-8.0.4.tar.gz", hash = "sha256:c0005a77a47d77889cafed892b58e33b4a2a96712154404c6548ec22272811ea"},
+]
[package.dependencies]
ipykernel = ">=4.5.1"
@@ -724,6 +1838,21 @@ widgetsnbextension = ">=4.0,<5.0"
[package.extras]
test = ["jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
+[[package]]
+name = "isoduration"
+version = "20.11.0"
+description = "Operations with ISO 8601 durations"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "isoduration-20.11.0-py3-none-any.whl", hash = "sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042"},
+ {file = "isoduration-20.11.0.tar.gz", hash = "sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9"},
+]
+
+[package.dependencies]
+arrow = ">=0.15.0"
+
[[package]]
name = "itsdangerous"
version = "2.1.2"
@@ -731,21 +1860,30 @@ description = "Safely pass data to untrusted environments and back."
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
+ {file = "itsdangerous-2.1.2-py3-none-any.whl", hash = "sha256:2c2349112351b88699d8d4b6b075022c0808887cb7ad10069318a8b0bc88db44"},
+ {file = "itsdangerous-2.1.2.tar.gz", hash = "sha256:5dbbc68b317e5e42f327f9021763545dc3fc3bfe22e6deb96aaf1fc38874156a"},
+]
[[package]]
name = "jedi"
-version = "0.18.1"
+version = "0.18.2"
description = "An autocompletion tool for Python that can be used for text editors."
category = "main"
optional = false
python-versions = ">=3.6"
+files = [
+ {file = "jedi-0.18.2-py2.py3-none-any.whl", hash = "sha256:203c1fd9d969ab8f2119ec0a3342e0b49910045abe6af0a3ae83a5764d54639e"},
+ {file = "jedi-0.18.2.tar.gz", hash = "sha256:bae794c30d07f6d910d32a7048af09b5a39ed740918da923c6b780790ebac612"},
+]
[package.dependencies]
parso = ">=0.8.0,<0.9.0"
[package.extras]
+docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
-testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<7.0.0)"]
+testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
[[package]]
name = "jinja2"
@@ -754,6 +1892,10 @@ description = "A very fast and expressive template engine."
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
+ {file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
+ {file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
+]
[package.dependencies]
MarkupSafe = ">=2.0"
@@ -768,20 +1910,48 @@ description = "Lightweight pipelining with Python functions"
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
+ {file = "joblib-1.2.0-py3-none-any.whl", hash = "sha256:091138ed78f800342968c523bdde947e7a305b8594b910a0fea2ab83c3c6d385"},
+ {file = "joblib-1.2.0.tar.gz", hash = "sha256:e1cee4a79e4af22881164f218d4311f60074197fb707e082e803b61f6d137018"},
+]
+
+[[package]]
+name = "jsonpointer"
+version = "2.3"
+description = "Identify specific nodes in a JSON document (RFC 6901)"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+ {file = "jsonpointer-2.3-py2.py3-none-any.whl", hash = "sha256:51801e558539b4e9cd268638c078c6c5746c9ac96bc38152d443400e4f3793e9"},
+ {file = "jsonpointer-2.3.tar.gz", hash = "sha256:97cba51526c829282218feb99dab1b1e6bdf8efd1c43dc9d57be093c0d69c99a"},
+]
[[package]]
name = "jsonschema"
-version = "4.16.0"
+version = "4.17.3"
description = "An implementation of JSON Schema validation for Python"
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
+ {file = "jsonschema-4.17.3-py3-none-any.whl", hash = "sha256:a870ad254da1a8ca84b6a2905cac29d265f805acc57af304784962a2aa6508f6"},
+ {file = "jsonschema-4.17.3.tar.gz", hash = "sha256:0f864437ab8b6076ba6707453ef8f98a6a0d512a80e93f8abdb676f737ecb60d"},
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[package.dependencies]
attrs = ">=17.4.0"
+fqdn = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+idna = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
+isoduration = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+jsonpointer = {version = ">1.13", optional = true, markers = "extra == \"format-nongpl\""}
pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
+rfc3339-validator = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""}
+uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-nongpl\""}
[package.extras]
format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -794,6 +1964,11 @@ description = "Jupyter metapackage. Install all the Jupyter components in one go
category = "main"
optional = false
python-versions = "*"
+files = [
+ {file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"},
+ {file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"},
+ {file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"},
+]
[package.dependencies]
ipykernel = "*"
@@ -805,86 +1980,154 @@ qtconsole = "*"
[[package]]
name = "jupyter-client"
-version = "7.4.3"
+version = "8.0.3"
description = "Jupyter protocol implementation and client libraries"
category = "main"
optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+ {file = "jupyter_client-8.0.3-py3-none-any.whl", hash = "sha256:be48ac6bd659cbbddb7a674cf06b3b8afbf53f228253cf58bde604c03bd487b0"},
+ {file = "jupyter_client-8.0.3.tar.gz", hash = "sha256:ed65498bea6d876ef9d8da3e0db3dd33c5d129f5b2645f56ae03993782966bd0"},
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[package.dependencies]
-entrypoints = "*"
-jupyter-core = ">=4.9.2"
-nest-asyncio = ">=1.5.4"
+importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
+jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
python-dateutil = ">=2.8.2"
pyzmq = ">=23.0"
tornado = ">=6.2"
-traitlets = "*"
+traitlets = ">=5.3"
[package.extras]
-doc = ["ipykernel", "myst-parser", "sphinx-rtd-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt"]
-test = ["codecov", "coverage", "ipykernel (>=6.12)", "ipython", "mypy", "pre-commit", "pytest", "pytest-asyncio (>=0.18)", "pytest-cov", "pytest-timeout"]
+docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["codecov", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
[[package]]
name = "jupyter-console"
-version = "6.4.4"
+version = "6.6.1"
description = "Jupyter terminal console"
category = "main"
optional = false
python-versions = ">=3.7"
+files = [
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+ {file = "jupyter_console-6.6.1.tar.gz", hash = "sha256:5931212d5cbc1f956f6fd615755b5e15f389a8eaa697288dbbe4377017615ecc"},
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ipython = "*"
jupyter-client = ">=7.0.0"
-prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0"
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+prompt-toolkit = ">=3.0.30"
pygments = "*"
+pyzmq = ">=17"
+traitlets = ">=5.4"
[package.extras]
-test = ["pexpect"]
+test = ["flaky", "pexpect", "pytest"]
[[package]]
name = "jupyter-core"
-version = "4.11.2"
+version = "5.2.0"
description = "Jupyter core package. A base package on which Jupyter projects rely."
category = "main"
optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
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+platformdirs = ">=2.5"
pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""}
-traitlets = "*"
+traitlets = ">=5.3"
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+docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
+[[package]]
+name = "jupyter-events"
+version = "0.6.3"
+description = "Jupyter Event System library"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
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+[package.dependencies]
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+python-json-logger = ">=2.0.4"
+pyyaml = ">=5.3"
+rfc3339-validator = "*"
+rfc3986-validator = ">=0.1.1"
+traitlets = ">=5.3"
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category = "main"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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optional = false
python-versions = ">=3.5.5"
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Pillow = ">=5.2.0"
tensorflow = ">=1.9.0"
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optional = false
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pyav = ["av"]
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optional = false
python-versions = ">=3.6"
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name = "tinycss2"
@@ -2161,26 +5447,72 @@ description = "A tiny CSS parser"
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python-versions = ">=3.7"
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python-versions = ">= 3.7"
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python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
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python-versions = ">=3.7"
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watchdog = ["watchdog"]
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- {file = "torchvision-0.12.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:36dfdf6451fe3072ab15118982853b848896c0fd3b26cb8135e1e7981dbb0916"},
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-]
-tornado = []
-tqdm = []
-traitlets = []
-transformers = []
-typing-extensions = []
-tzdata = []
-tzlocal = [
- {file = "tzlocal-4.2-py3-none-any.whl", hash = "sha256:89885494684c929d9191c57aa27502afc87a579be5cdd3225c77c463ea043745"},
- {file = "tzlocal-4.2.tar.gz", hash = "sha256:ee5842fa3a795f023514ac2d801c4a81d1743bbe642e3940143326b3a00addd7"},
-]
-umap-learn = [
- {file = "umap-learn-0.5.3.tar.gz", hash = "sha256:dbd57cb181c2b66d238acb5635697526bf24c798082daed0cf9b87f6a3a6c0c7"},
-]
-urllib3 = []
-validators = []
-watchdog = []
-wcwidth = [
- {file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
- {file = "wcwidth-0.2.5.tar.gz", hash = "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"},
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-webencodings = [
- {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
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-]
-websocket-client = []
-werkzeug = []
-widgetsnbextension = []
-wrapt = []
-zipp = []
+lock-version = "2.0"
+python-versions = ">=3.8,<3.9.7 || >3.9.7,<3.11"
+content-hash = "e1ae1b4a520eb0db9d1f2fcf591426c52584d236505d40fc79bc5ed002593838"
diff --git a/pyproject.toml b/pyproject.toml
index c2d3c42..2f50462 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,12 +1,12 @@
[tool.poetry]
name = "bechdelai"
-version = "0.0.1-alpha.2"
+version = "0.0.2"
description = "Automating the Bechdel test and its variants for feminine representation in movies with AI"
authors = ["Data For Good "]
license = "MIT"
[tool.poetry.dependencies]
-python = ">=3.8,<3.9.7 || >3.9.7,<3.10"
+python = ">=3.8,<3.9.7 || >3.9.7,<3.11"
jupyter = "^1.0.0"
pandas = "^1.3.4"
numpy = "^1.21.3"
@@ -35,9 +35,17 @@ openpyxl = "^3.0.10"
pytube = "^12.1.0"
mediapipe = "^0.9.0"
scenedetect = {extras = ["opencv"], version = "^0.6.1"}
+moviepy = "^1.0.3"
+SpeechRecognition = "^3.8.1"
+inaSpeechSegmenter = "^0.7.3"
+llvmlite = "^0.39.1"
+setuptools = ">=62.3.2"
+openai = "^0.27.0"
+openai-whisper = "^20230307"
+gradio = "^3.20.1"
[tool.poetry.dev-dependencies]
-pywin32 = { version = "225", markers = "sys_platform == 'win32'" }
+pywin32 = { version = "305", markers = "sys_platform == 'win32'" }
jupyter = "^1.0.0"
mkdocs = "^1.4.1"
streamlit = "1.13.0"
diff --git a/tutorials/drafts/Tutorial - Bechdel test demo for ODI.ipynb b/tutorials/drafts/Tutorial - Bechdel test demo for ODI.ipynb
new file mode 100644
index 0000000..708a3ac
--- /dev/null
+++ b/tutorials/drafts/Tutorial - Bechdel test demo for ODI.ipynb
@@ -0,0 +1,3468 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "c8e95d37",
+ "metadata": {},
+ "source": [
+ "# Bechdel test demo for ODI"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "b6ae2322",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:39.068583Z",
+ "start_time": "2023-03-22T11:14:30.202780Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "2023-03-22 12:14:32.847758: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA\n",
+ "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+ "2023-03-22 12:14:33.329973: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+ "2023-03-22 12:14:33.393221: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
+ "2023-03-22 12:14:33.393247: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n",
+ "2023-03-22 12:14:34.967464: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
+ "2023-03-22 12:14:34.967590: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
+ "2023-03-22 12:14:34.967596: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
+ ]
+ }
+ ],
+ "source": [
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "import sys\n",
+ "sys.path.append(\"../../\")\n",
+ "\n",
+ "%load_ext autoreload\n",
+ "%autoreload 2\n",
+ "\n",
+ "import bechdelai\n",
+ "from bechdelai.audio import config, utils\n",
+ "from bechdelai.audio.audio_processor import AudioProcessor"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "53259d8b",
+ "metadata": {},
+ "source": [
+ "# Bechdel test on movie trailer"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "ed5b9e67",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:39.139370Z",
+ "start_time": "2023-03-22T11:14:39.071933Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "trailer_avengers = \"https://www.youtube.com/watch?v=TcMBFSGVi1c&ab_channel=MarvelEntertainment\"\n",
+ "trailer_littlewomen = \"https://www.youtube.com/watch?v=AST2-4db4ic&ab_channel=SonyPicturesEntertainment\"\n",
+ "trailer_moncrime = \"https://www.youtube.com/watch?v=PaNkAPIUvpA\"\n",
+ "trailer_empire = \"https://www.youtube.com/watch?v=3JA3bD5xs-Q\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "8e998bba",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:39.292229Z",
+ "start_time": "2023-03-22T11:14:39.142129Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " VIDEO \n",
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from bechdelai.data.youtube import show_youtube_in_notebook\n",
+ "\n",
+ "show_youtube_in_notebook(trailer_littlewomen)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "905bbf1d",
+ "metadata": {},
+ "source": [
+ "## Download trailer from Youtube and convert to audio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "f9a46736",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:39.375613Z",
+ "start_time": "2023-03-22T11:14:39.295785Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from bechdelai.data.youtube import download_youtube_video\n",
+ "from bechdelai.audio.utils import extract_audio_from_video"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "a268ab19",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:42.004113Z",
+ "start_time": "2023-03-22T11:14:39.380756Z"
+ },
+ "hide_input": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Saved the youtube video at video.mp4\n"
+ ]
+ }
+ ],
+ "source": [
+ "download_youtube_video(trailer_littlewomen,\"video.mp4\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "8b86a4c3",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:55.167123Z",
+ "start_time": "2023-03-22T11:14:51.224544Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "MoviePy - Writing audio in video.mp3\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ " "
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "MoviePy - Done.\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\r"
+ ]
+ }
+ ],
+ "source": [
+ "extract_audio_from_video(\"video.mp4\",\"mp3\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "c41331e0",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:55.253979Z",
+ "start_time": "2023-03-22T11:14:55.170789Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# from IPython.display import Audio\n",
+ "# Audio(\"video.wav\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0b4f6beb",
+ "metadata": {},
+ "source": [
+ "## Audio pipeline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "de546464",
+ "metadata": {},
+ "source": [
+ "### Speech to text"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "ceac02ca",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:55.319875Z",
+ "start_time": "2023-03-22T11:14:55.256503Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from bechdelai.audio.transcriber import WhisperAPI"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "d9e630a5",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:14:55.404907Z",
+ "start_time": "2023-03-22T11:14:55.323840Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "whisper_api = WhisperAPI()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "e31c2d16",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:07.572409Z",
+ "start_time": "2023-03-22T11:14:55.410220Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
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+ " \n",
+ " \n",
+ " \n",
+ " start \n",
+ " end \n",
+ " text \n",
+ " speech \n",
+ " \n",
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+ " start end text speech\n",
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+ ],
+ "source": [
+ "result,segments,text = whisper_api.speech_to_text(\"video.mp3\")\n",
+ "segments.head()"
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+ {
+ "cell_type": "code",
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+ "end_time": "2023-03-22T11:15:07.657408Z",
+ "start_time": "2023-03-22T11:15:07.577029Z"
+ }
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+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "58241511",
+ "metadata": {},
+ "source": [
+ "### Gender classification post speech to text"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "6bc45a70",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:07.735909Z",
+ "start_time": "2023-03-22T11:15:07.662605Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from bechdelai.audio.gender_segmenter import InaSpeechSegmentor"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "3d9e4ee5",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:08.263034Z",
+ "start_time": "2023-03-22T11:15:07.739258Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "2023-03-22 12:15:07.806262: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /root/.cache/pypoetry/virtualenvs/bechdelai-aAZXO16a-py3.9/lib/python3.9/site-packages/cv2/../../lib64:\n",
+ "2023-03-22 12:15:07.806739: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)\n",
+ "2023-03-22 12:15:07.806772: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (EKI-PC81XSYD3): /proc/driver/nvidia/version does not exist\n",
+ "2023-03-22 12:15:07.808251: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA\n",
+ "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
+ ]
+ }
+ ],
+ "source": [
+ "gender = InaSpeechSegmentor(only_gender=True,batch_size = 32)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "46d71575",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:25.711801Z",
+ "start_time": "2023-03-22T11:15:08.264739Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "186/186 - 15s - 15s/epoch - 81ms/step\n"
+ ]
+ }
+ ],
+ "source": [
+ "segments_ina = gender._convert_whisper_output(segments)\n",
+ "segments_ina = gender.predict_gender_on_segments(\"video.mp3\",segments_ina)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "251a3051",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:25.785484Z",
+ "start_time": "2023-03-22T11:15:25.714718Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " start \n",
+ " end \n",
+ " text \n",
+ " speech \n",
+ " gender \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
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+ " 0.0 \n",
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+ " 4 \n",
+ " 11.0 \n",
+ " 14.0 \n",
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+ " ... \n",
+ " ... \n",
+ " \n",
+ " \n",
+ " 57 \n",
+ " 123.0 \n",
+ " 125.5 \n",
+ " that love is just all a woman is fit for. \n",
+ " True \n",
+ " female \n",
+ " \n",
+ " \n",
+ " 58 \n",
+ " 125.5 \n",
+ " 127.0 \n",
+ " I'm so sick of it. \n",
+ " True \n",
+ " female \n",
+ " \n",
+ " \n",
+ " 59 \n",
+ " 127.0 \n",
+ " 139.0 \n",
+ " βͺβͺ \n",
+ " False \n",
+ " NaN \n",
+ " \n",
+ " \n",
+ " 60 \n",
+ " 139.0 \n",
+ " 142.5 \n",
+ " There are some natures too lofty to bend. \n",
+ " True \n",
+ " male \n",
+ " \n",
+ " \n",
+ " 61 \n",
+ " 142.5 \n",
+ " 149.5 \n",
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+ " True \n",
+ " male \n",
+ " \n",
+ " \n",
+ "
\n",
+ "
62 rows Γ 5 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " start end text speech gender\n",
+ "0 0.0 3.0 This is Meg, Amy, Beth, and Joe. True male\n",
+ "1 3.0 5.5 βͺβͺ False NaN\n",
+ "2 5.5 9.5 βͺβͺ False NaN\n",
+ "3 9.5 11.0 I'm working on a novel. True female\n",
+ "4 11.0 14.0 It is a story of my life and my sisters. True female\n",
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+ "58 125.5 127.0 I'm so sick of it. True female\n",
+ "59 127.0 139.0 βͺβͺ False NaN\n",
+ "60 139.0 142.5 There are some natures too lofty to bend. True male\n",
+ "61 142.5 149.5 So, who does she marry? True male\n",
+ "\n",
+ "[62 rows x 5 columns]"
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "segments_with_gender = segments.merge(segments_ina[[\"gender\",\"start\"]],on = \"start\",how = \"left\")\n",
+ "segments_with_gender"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "005dcea2",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:25.858000Z",
+ "start_time": "2023-03-22T11:15:25.788432Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "segments_with_gender[\"duration\"] = segments_with_gender[\"end\"] - segments_with_gender[\"start\"]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "04afc903",
+ "metadata": {},
+ "source": [
+ "## Dialogue detection"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "fadf57f7",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:25.916945Z",
+ "start_time": "2023-03-22T11:15:25.859868Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "pd.set_option('display.max_rows', 100)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "fa7a9203",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:25.996671Z",
+ "start_time": "2023-03-22T11:15:25.919745Z"
+ }
+ },
+ "outputs": [
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+ " start end text speech gender \\\n",
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+ "dialogue_id = segments_with_gender[\"speech\"].astype(int).diff(1).fillna(0)\n",
+ "dialogue_id.loc[dialogue_id < 0] = 0\n",
+ "segments_with_gender[\"dialogue_id\"] = dialogue_id.cumsum()\n",
+ "segments_with_gender.loc[segments_with_gender[\"speech\"] == False,\"dialogue_id\"] = np.NaN\n",
+ "\n",
+ "segments_with_gender.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "585cfa42",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:26.079777Z",
+ "start_time": "2023-03-22T11:15:26.001520Z"
+ }
+ },
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+ {
+ "data": {
+ "text/plain": [
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+ },
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+ "\n",
+ "px.pie(\n",
+ " segments_with_gender.groupby(\"gender\")[\"duration\"].sum().reset_index(),\n",
+ " values = \"duration\",\n",
+ " names = \"gender\",\n",
+ " color = \"gender\",\n",
+ " color_discrete_map={\"female\":\"#acef9f\",\"male\":\"#FF4D4D\"},\n",
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+ "id": "d1c48a13",
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+ "start_time": "2023-03-22T11:15:27.203733Z"
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+ },
+ "xaxis": {
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+ 0,
+ 1
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+ },
+ "yaxis": {
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+ "source": [
+ "timeline = segments_with_gender.copy()\n",
+ "timeline[\"start_time\"] = timeline[\"start\"].map(lambda x : pd.Timedelta(seconds = x))\n",
+ "timeline[\"end_time\"] = timeline[\"end\"].map(lambda x : pd.Timedelta(seconds = x))\n",
+ "start_date = pd.to_datetime(\"2022-01-01\")\n",
+ "timeline[\"start_time\"] = start_date + timeline[\"start_time\"]\n",
+ "timeline[\"end_time\"] = start_date + timeline[\"end_time\"]\n",
+ "\n",
+ "px.timeline(\n",
+ " timeline,\n",
+ " x_start = \"start_time\",\n",
+ " x_end = \"end_time\",\n",
+ " color = \"gender\",\n",
+ " y = \"dialogue_id\",\n",
+ " color_discrete_map={\"female\":\"#acef9f\",\"male\":\"#FF4D4D\"},\n",
+ " title = \"Timeline du temps de parole\"\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "b36643f2",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:27.418289Z",
+ "start_time": "2023-03-22T11:15:27.350726Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " gender \n",
+ " female \n",
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+ "gender female male\n",
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+ "execution_count": 23,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "segments_with_gender.groupby([\"dialogue_id\",\"gender\"])[\"duration\"].sum().unstack(\"gender\").fillna(0.0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "ddb0336f",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:27.508375Z",
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+ {
+ "data": {
+ "text/html": [
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+ " start end\n",
+ "dialogue_id \n",
+ "0.0 0.0 3.0\n",
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+ "2.0 22.5 50.5\n",
+ "3.0 53.0 62.0\n",
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+ "6.0 79.5 127.0\n",
+ "7.0 139.0 149.5"
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+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "segments_with_gender.groupby([\"dialogue_id\"]).agg({\"start\":\"min\",\"end\":\"max\"})"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3e8febf9",
+ "metadata": {},
+ "source": [
+ "# 3rd question of the test with GPT-3"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "id": "3834eb81",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:31:13.268215Z",
+ "start_time": "2023-03-22T11:31:13.200954Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "female: I'm working on a novel.\n",
+ "female: It is a story of my life and my sisters.\n",
+ "male: Make it short and spicy.\n",
+ "male: And if the main character is a girl,\n",
+ "male: make sure she's married by the end.\n",
+ "male: Ow, Joe!\n"
+ ]
+ }
+ ],
+ "source": [
+ "text = []\n",
+ "for i,row in segments_with_gender.query(\"dialogue_id == 1\").iterrows():\n",
+ " text.append(f\"{row['gender']}: {row['text']}\")\n",
+ "text = \"\\n\".join(text)\n",
+ "print(text)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "07ab8cd6",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:34.155866Z",
+ "start_time": "2023-03-22T11:15:34.050367Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from bechdelai.nlp.gpt import GPT3"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "id": "68b32397",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:34.656408Z",
+ "start_time": "2023-03-22T11:15:34.584850Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "gpt = GPT3()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "ceec4eff",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:44.209303Z",
+ "start_time": "2023-03-22T11:15:35.037531Z"
+ },
+ "code_folding": []
+ },
+ "outputs": [],
+ "source": [
+ "answers = gpt.answer_questions([\n",
+ " \"Are they talking about a man?\",\n",
+ " \"Are they talking about romance?\",\n",
+ " \"what stereotypes towards women are conveyed in this dialogue?\"\n",
+ "],text)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "0cb1ff94",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-03-22T11:15:44.280685Z",
+ "start_time": "2023-03-22T11:15:44.211320Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Are they talking about a man?\n",
+ "\n",
+ "No, they are not talking about a man. The dialogue is introducing four people by their names, three of whom are female (Meg, Amy, Beth) and one of whom is male (Joe). This suggests that the dialogue is not focused on the male character, but rather is introducing the four people collectively.\n",
+ "------------------------------\n",
+ "Are they talking about romance?\n",
+ "\n",
+ "No, they are not talking about romance. The dialogue is introducing four people - Meg, Amy, Beth and Joe - without any context as to why they are being introduced. There is no indication of any kind of romantic relationship between the individuals, so it is safe to assume that they are not talking about romance.\n",
+ "------------------------------\n",
+ "what stereotypes towards women are conveyed in this dialogue?\n",
+ "\n",
+ "The dialogue conveys a stereotype that women are only seen in relation to other people, specifically other women, which implies that they are not seen as individuals in their own right. Additionally, the dialogue implies that women are often grouped together rather than seen as individual characters, which is another stereotype. Finally, the dialogue implies that women are often seen as part of a group rather than as individuals, which can be seen as a reinforcement of the idea that women are subordinate to men.\n",
+ "------------------------------\n"
+ ]
+ }
+ ],
+ "source": [
+ "for i,row in answers.iterrows():\n",
+ " print(row[\"question\"])\n",
+ " print(row[\"answer\"])\n",
+ " print(\"------------------------------\")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.13"
+ },
+ "toc": {
+ "base_numbering": 1,
+ "nav_menu": {},
+ "number_sections": true,
+ "sideBar": true,
+ "skip_h1_title": false,
+ "title_cell": "Table of Contents",
+ "title_sidebar": "Contents",
+ "toc_cell": false,
+ "toc_position": {
+ "height": "calc(100% - 180px)",
+ "left": "10px",
+ "top": "150px",
+ "width": "165px"
+ },
+ "toc_section_display": true,
+ "toc_window_display": false
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/drafts/Tutorial - Get dialogues from audio with gender timeranges.ipynb b/tutorials/drafts/Tutorial - Get dialogues from audio with gender timeranges.ipynb
new file mode 100644
index 0000000..73facc8
--- /dev/null
+++ b/tutorials/drafts/Tutorial - Get dialogues from audio with gender timeranges.ipynb
@@ -0,0 +1,1114 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "c8e95d37",
+ "metadata": {},
+ "source": [
+ "# Tutorial - Get dialogues from audio with gender timeranges"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "b6ae2322",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "sys.path.append(\"../../\")\n",
+ "\n",
+ "import bechdelai\n",
+ "from bechdelai.audio import config, utils\n",
+ "from bechdelai.audio.audio_processor import AudioProcessor"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "53259d8b",
+ "metadata": {},
+ "source": [
+ "## Download the trailer from Youtube\n",
+ "We are going to use the get_youtube function inspired from https://huggingface.co/spaces/Karwasze/Whisper-ASR-youtube-subtitles/blob/main/app.py"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "36099133",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from pytube import YouTube\n",
+ "\n",
+ "def get_youtube(video_url):\n",
+ " \"\"\"Download youtube video from a given url\"\"\"\n",
+ " yt = YouTube(video_url)\n",
+ " abs_video_path = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first().download()\n",
+ " \n",
+ " return abs_video_path"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "48d886c3",
+ "metadata": {},
+ "source": [
+ "For the purpose of this tutorial we are, firt, choosing a French movie : Les Tuche 4"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "a268ab19",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "video_url = \"https://www.youtube.com/watch?v=TCTtdSuj2eo&ab_channel=FilmsActu\" #Tuche 4\n",
+ "video_path = get_youtube(video_url)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "63ee3d3d",
+ "metadata": {},
+ "source": [
+ "## Convert movie to audio\n",
+ "We must now isolate the audio file with a `.wav` format."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "2ffcd44e",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "MoviePy - Writing audio in C:\\Users\\chloe\\Documents\\DATAFORGOOD\\bechdelai\\tutorials\\drafts\\LES TUCHE 4 Bande Annonce Officielle (2021).wav\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ " "
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "MoviePy - Done.\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\r"
+ ]
+ }
+ ],
+ "source": [
+ "utils.extract_audio_from_movie(video_path)\n",
+ "audio_path = video_path.split(sep='.')[0] + '.wav'"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c8693be4",
+ "metadata": {},
+ "source": [
+ "## Load audio processing for French\n",
+ "The first step is to set the configuration according to the language. In the next versions it will also be possible to choose speed for example."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "44e5258f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "configuration = config.Config()\n",
+ "configuration.select_profile(option=\"FR\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "4b59a1cb",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "configuration.get_profile()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "7f536f7d",
+ "metadata": {},
+ "source": [
+ "Once the language is set, it's time to run the machine..."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "60233231",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "149/149 - 3s - 3s/epoch - 20ms/step\n",
+ "111/111 - 5s - 5s/epoch - 43ms/step\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92710316,\n",
+ " 'transcript': \"NoΓ«l c'est comme les frites c'est \"\n",
+ " 'quand on veut'},\n",
+ " { 'transcript': \"NoΓ«l c'est comme les frites c'est \"\n",
+ " 'quand ton vΕu'},\n",
+ " { 'transcript': \"NoΓ«l c'est comme les frites c'est \"\n",
+ " 'quand ton vΕux'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.9121725,\n",
+ " 'transcript': \"bonjour c'est nous les Tuche\"},\n",
+ " {'transcript': \"bonjour c'est nous les tuches\"},\n",
+ " {'transcript': \"bonjour c'est nous les Tuche après\"}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.89889336,\n",
+ " 'transcript': \"donc c'est nous les Tuche\"},\n",
+ " {'transcript': \"c'est nous les Tuche\"},\n",
+ " {'transcript': \"donc c'est nous les tuches\"}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92710316,\n",
+ " 'transcript': \"exactement c'est le moment de \"\n",
+ " 'prΓ©parer NoΓ«l en famille'},\n",
+ " { 'transcript': \"exactement c'est le moment de \"\n",
+ " 'prΓ©parer NoΓ«l en famille dis-moi ce'},\n",
+ " { 'transcript': \"exactement c'est le moment de \"\n",
+ " 'prΓ©parer NoΓ«l en famille dis-moi ce '\n",
+ " 'qui'},\n",
+ " { 'transcript': \"exactement c'est le moment de \"\n",
+ " 'prΓ©parer NoΓ«l en famille dis-moi'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.9117986,\n",
+ " 'transcript': 'dis-moi ce qui se passe je voudrais'},\n",
+ " {'transcript': 'je voudrais'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92420292,\n",
+ " 'transcript': 'dis-moi ce qui se passe quand je '\n",
+ " 'voudrais que ma sΕur soit il a aussi '\n",
+ " 'problème tous les deux là pour des '\n",
+ " 'conneries il y a 10 ans'},\n",
+ " { 'transcript': 'dis-moi ce qui se passe quand je '\n",
+ " 'voudrais que ma sΕur soit il a aussi '\n",
+ " 'problème à tous les deux là pour des '\n",
+ " 'conneries il y a 10 ans'},\n",
+ " { 'transcript': 'dis-moi ce qui se passe quand je '\n",
+ " 'voudrais que ma sΕur soit il a aussi '\n",
+ " 'problème tous les deux là pour des '\n",
+ " 'conneries il y a 10 ans alors'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92171675,\n",
+ " 'transcript': 'il y a 10 ans alors marteau tu as '\n",
+ " 'toujours ton travail je me rΓ©gale '\n",
+ " 'ces magasins'},\n",
+ " { 'transcript': 'il y a 10 ans alors marteau tu es '\n",
+ " 'toujours ton travail je me rΓ©gale '\n",
+ " 'ces magasins'},\n",
+ " { 'transcript': 'il y a 10 ans alors marteau tu as '\n",
+ " 'toujours ton travail je me rΓ©gale '\n",
+ " 'ces magasins 2 x'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92710316,\n",
+ " 'transcript': \"qu'est-ce que je disais dΓ©jΓ \"},\n",
+ " { 'transcript': \"ouvrir l'ennemi qu'est-ce que je \"\n",
+ " 'disais dΓ©jΓ '},\n",
+ " { 'transcript': \"ouvrir l'ennemi qu'est-ce que je \"\n",
+ " 'disais dΓ©jΓ Γ©coutΓ© pas'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.85335368,\n",
+ " 'transcript': \"je vois j'Γ©coutais pas Γ§a va\"},\n",
+ " {'transcript': \"c'est bon j'Γ©coutais pas Γ§a va\"},\n",
+ " {'transcript': \"je vois j'Γ©coutais pas Γ§a va Γͺtre\"}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.9271031,\n",
+ " 'transcript': 'Γ§a va Γͺtre long'},\n",
+ " {'transcript': 'Γ§a va Γͺtre longue'},\n",
+ " {'transcript': 'Γ§a va Γͺtre long lΓ '}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.91169006,\n",
+ " 'transcript': \"il y a plus d'usine des jouets \"\n",
+ " 'devant vous vendez Γ qui'},\n",
+ " { 'transcript': \"il y a plus d'usine des jouets \"\n",
+ " 'devant vous vous vendez Γ qui'},\n",
+ " { 'transcript': \"il y a plus d'usine des jouets je \"\n",
+ " 'vends vous vendez Γ qui'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.89714372,\n",
+ " 'transcript': 'les gros gagne les petits meurent '\n",
+ " 'vous Γͺtes dans la deuxiΓ¨me catΓ©gorie '\n",
+ " 'dΓ©solΓ©'},\n",
+ " { 'transcript': 'les gros gagnent les petits meurent '\n",
+ " 'vous Γͺtes dans la deuxiΓ¨me catΓ©gorie '\n",
+ " 'dΓ©solΓ©'},\n",
+ " { 'transcript': 'les gros gagne les petits meurent '\n",
+ " 'vous Γͺtes dans la deuxiΓ¨me catΓ©gorie '\n",
+ " 'dΓ©solΓ©e'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.91114563,\n",
+ " 'transcript': \"j'ai une proposition Γ vous faire \"\n",
+ " 'voilΓ mon plan racheter limarolles '\n",
+ " 'et fabriquer des jouets en bois '\n",
+ " \"qu'est-ce que tu voulais avoir toi \"\n",
+ " 'tu veux des clous il fabrique un '\n",
+ " \"jouet que nous n'avons pas vous \"\n",
+ " \"pourriez appeler l'inspection du \"\n",
+ " 'travail lΓ vous travaillez monsieur '\n",
+ " 'Tuche non je travaille pas je suis '\n",
+ " 'pas trop vous avez dΓ©jΓ vu un patron '\n",
+ " 'qui travaille vous'},\n",
+ " { 'transcript': \"j'ai une proposition Γ vous faire \"\n",
+ " 'voilΓ mon plan racheter limarolles '\n",
+ " 'et fabriquer des jouets en bois '\n",
+ " \"qu'est-ce que tu voulais avoir toi \"\n",
+ " 'tu veux des clous il fabrique un '\n",
+ " \"jouet que nous n'avons pas vous \"\n",
+ " \"pourriez appeler l'inspection du \"\n",
+ " 'travail lΓ vous travaillez monsieur '\n",
+ " 'Tuche pas trop vous avez dΓ©jΓ vu un '\n",
+ " 'patron qui travaille vous'},\n",
+ " { 'transcript': \"j'ai une proposition Γ vous faire \"\n",
+ " 'voilΓ mon plan racheter limarolles '\n",
+ " 'et fabriquer des jouets en bois '\n",
+ " \"qu'est-ce que tu voulais avoir toi \"\n",
+ " 'tu veux des clous il fabrique un '\n",
+ " \"jouet que nous n'avons pas vous \"\n",
+ " \"pourriez appeler l'inspection du \"\n",
+ " 'travail lΓ vous travaillez monsieur '\n",
+ " 'Tuche pas trop vous avez dΓ©jΓ vu un '\n",
+ " 'patron qui travaille'}],\n",
+ " 'final': True}\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92594719,\n",
+ " 'transcript': \"ah c'est les Γ©chos tu connais tu \"\n",
+ " 'connais tu connais de quoi de quoi '\n",
+ " \"ah ok j'y suis très drôle\"},\n",
+ " { 'transcript': \"ah c'est les Γ©chos tu connais tu \"\n",
+ " 'connais tu connais de quoi de quoi '\n",
+ " \"ah ok j'y suis très drôles\"},\n",
+ " { 'transcript': \"ah c'est les Γ©chos tu connais tu \"\n",
+ " 'connais tu connais de quoi de quoi '\n",
+ " \"ah ok j'y suis les échos très \"\n",
+ " 'drΓ΄les'}],\n",
+ " 'final': True}\n"
+ ]
+ }
+ ],
+ "source": [
+ "import time\n",
+ "t0 = time.time()\n",
+ "ap = AudioProcessor(configuration, audio_path)\n",
+ "t1 = time.time()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "10740556",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'Execution time : 65.41201686859131 seconds.'"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\"Execution time : {} seconds.\".format(t1-t0)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8d446e99",
+ "metadata": {},
+ "source": [
+ "To write all the results properly.. :)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "cb526782",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " gender \n",
+ " start \n",
+ " end \n",
+ " transcription \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 \n",
+ " male \n",
+ " 0.32 \n",
+ " 3.06 \n",
+ " NoΓ«l c'est comme les frites c'est quand on veut \n",
+ " \n",
+ " \n",
+ " 1 \n",
+ " female \n",
+ " 5.14 \n",
+ " 6.60 \n",
+ " bonjour c'est nous les Tuche \n",
+ " \n",
+ " \n",
+ " 2 \n",
+ " male \n",
+ " 6.60 \n",
+ " 7.90 \n",
+ " donc c'est nous les Tuche \n",
+ " \n",
+ " \n",
+ " 3 \n",
+ " female \n",
+ " 7.90 \n",
+ " 13.60 \n",
+ " exactement c'est le moment de prΓ©parer NoΓ«l en famille \n",
+ " \n",
+ " \n",
+ " 4 \n",
+ " male \n",
+ " 13.60 \n",
+ " 14.92 \n",
+ " dis-moi ce qui se passe je voudrais \n",
+ " \n",
+ " \n",
+ " 5 \n",
+ " female \n",
+ " 14.92 \n",
+ " 24.32 \n",
+ " dis-moi ce qui se passe quand je voudrais que ma sΕur soit il a aussi problΓ¨me tous les deux lΓ pour des conneries il y a 10 ans \n",
+ " \n",
+ " \n",
+ " 6 \n",
+ " male \n",
+ " 24.32 \n",
+ " 34.86 \n",
+ " il y a 10 ans alors marteau tu as toujours ton travail je me rΓ©gale ces magasins \n",
+ " \n",
+ " \n",
+ " 7 \n",
+ " male \n",
+ " 38.72 \n",
+ " 40.62 \n",
+ " qu'est-ce que je disais dΓ©jΓ \n",
+ " \n",
+ " \n",
+ " 8 \n",
+ " female \n",
+ " 40.62 \n",
+ " 42.36 \n",
+ " je vois j'Γ©coutais pas Γ§a va \n",
+ " \n",
+ " \n",
+ " 9 \n",
+ " male \n",
+ " 42.36 \n",
+ " 43.60 \n",
+ " Γ§a va Γͺtre long \n",
+ " \n",
+ " \n",
+ " 10 \n",
+ " male \n",
+ " 49.52 \n",
+ " 52.00 \n",
+ " il y a plus d'usine des jouets devant vous vendez Γ qui \n",
+ " \n",
+ " \n",
+ " 11 \n",
+ " male \n",
+ " 54.70 \n",
+ " 58.62 \n",
+ " les gros gagne les petits meurent vous Γͺtes dans la deuxiΓ¨me catΓ©gorie dΓ©solΓ© \n",
+ " \n",
+ " \n",
+ " 12 \n",
+ " male \n",
+ " 60.24 \n",
+ " 77.70 \n",
+ " j'ai une proposition Γ vous faire voilΓ mon plan racheter limarolles et fabriquer des jouets en bois qu'est-ce que tu voulais avoir toi tu veux des clous il fabrique un jouet que nous n'avons pas vous pourriez appeler l'inspection du travail lΓ vous travaillez monsieur Tuche non je travaille pas je suis pas trop vous avez dΓ©jΓ vu un patron qui travaille vous \n",
+ " \n",
+ " \n",
+ " 13 \n",
+ " male \n",
+ " 85.56 \n",
+ " 95.32 \n",
+ " ah c'est les échos tu connais tu connais tu connais de quoi de quoi ah ok j'y suis très drôle \n",
+ " \n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " gender start end \\\n",
+ "0 male 0.32 3.06 \n",
+ "1 female 5.14 6.60 \n",
+ "2 male 6.60 7.90 \n",
+ "3 female 7.90 13.60 \n",
+ "4 male 13.60 14.92 \n",
+ "5 female 14.92 24.32 \n",
+ "6 male 24.32 34.86 \n",
+ "7 male 38.72 40.62 \n",
+ "8 female 40.62 42.36 \n",
+ "9 male 42.36 43.60 \n",
+ "10 male 49.52 52.00 \n",
+ "11 male 54.70 58.62 \n",
+ "12 male 60.24 77.70 \n",
+ "13 male 85.56 95.32 \n",
+ "\n",
+ " transcription \n",
+ "0 NoΓ«l c'est comme les frites c'est quand on veut \n",
+ "1 bonjour c'est nous les Tuche \n",
+ "2 donc c'est nous les Tuche \n",
+ "3 exactement c'est le moment de prΓ©parer NoΓ«l en famille \n",
+ "4 dis-moi ce qui se passe je voudrais \n",
+ "5 dis-moi ce qui se passe quand je voudrais que ma sΕur soit il a aussi problΓ¨me tous les deux lΓ pour des conneries il y a 10 ans \n",
+ "6 il y a 10 ans alors marteau tu as toujours ton travail je me rΓ©gale ces magasins \n",
+ "7 qu'est-ce que je disais dΓ©jΓ \n",
+ "8 je vois j'Γ©coutais pas Γ§a va \n",
+ "9 Γ§a va Γͺtre long \n",
+ "10 il y a plus d'usine des jouets devant vous vendez Γ qui \n",
+ "11 les gros gagne les petits meurent vous Γͺtes dans la deuxiΓ¨me catΓ©gorie dΓ©solΓ© \n",
+ "12 j'ai une proposition Γ vous faire voilΓ mon plan racheter limarolles et fabriquer des jouets en bois qu'est-ce que tu voulais avoir toi tu veux des clous il fabrique un jouet que nous n'avons pas vous pourriez appeler l'inspection du travail lΓ vous travaillez monsieur Tuche non je travaille pas je suis pas trop vous avez dΓ©jΓ vu un patron qui travaille vous \n",
+ "13 ah c'est les échos tu connais tu connais tu connais de quoi de quoi ah ok j'y suis très drôle "
+ ]
+ },
+ "execution_count": 16,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import pandas as pd\n",
+ "pd.set_option('display.max_colwidth', None) # To see the whole transcription\n",
+ "\n",
+ "ap.full_dataframe()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3d627dd7",
+ "metadata": {},
+ "source": [
+ "## Do the same with English\n",
+ "Let's analyse..."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "68c95c97",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "MoviePy - Writing audio in C:\\Users\\chloe\\Documents\\DATAFORGOOD\\bechdelai\\tutorials\\drafts\\Letitia Wright reacts to Shuri getting snapped by Thanos LIVE from the Avengers Endgame Premiere.wav\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ " "
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "MoviePy - Done.\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\r"
+ ]
+ }
+ ],
+ "source": [
+ "video_url_en = \"https://www.youtube.com/watch?v=9nusLMvCTsI\" # Interview Laetitia Wright\n",
+ "video_path_en = get_youtube(video_url_en)\n",
+ "utils.extract_audio_from_movie(video_path_en)\n",
+ "audio_path_en = video_path_en.split(sep='.')[0] + '.wav'\n",
+ "configuration_en = config.Config()\n",
+ "configuration_en.select_profile(option=\"US\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "c7e4d37c",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "167/167 - 3s - 3s/epoch - 21ms/step\n",
+ "167/167 - 7s - 7s/epoch - 43ms/step\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.94617063,\n",
+ " 'transcript': \"oh my gosh she is here but it's \"\n",
+ " 'alright how are you doing this '\n",
+ " \"evening very well I'm coming here I \"\n",
+ " \"don't know what to expect but I'm \"\n",
+ " 'having a good time already ok we '\n",
+ " 'have to talk some tea right now '\n",
+ " 'which is we saw the posters there '\n",
+ " 'was an outcry what was it like for '\n",
+ " 'you it was it was surprising I saw '\n",
+ " 'everybody in like you know the '\n",
+ " 'coloured photos in a coloured '\n",
+ " \"posters and then it's all my stuff \"\n",
+ " 'in grey and I was like you I just '\n",
+ " 'died'},\n",
+ " { 'transcript': \"oh my gosh Shirley is here but it's \"\n",
+ " 'alright how are you doing this '\n",
+ " \"evening very well I'm coming here I \"\n",
+ " \"don't know what to expect but I'm \"\n",
+ " 'having a good time already ok we '\n",
+ " 'have to talk some tea right now '\n",
+ " 'which is we saw the posters there '\n",
+ " 'was an outcry what was it like for '\n",
+ " 'you it was it was surprising I saw '\n",
+ " 'everybody in like you know the '\n",
+ " 'coloured photos in a coloured '\n",
+ " 'posters and it is all my stuff in '\n",
+ " 'grey and I was like you I just died'},\n",
+ " { 'transcript': \"oh my gosh she is here but it's \"\n",
+ " 'alright how are you doing this '\n",
+ " \"evening very well I'm coming here I \"\n",
+ " \"don't know what to expect but I'm \"\n",
+ " 'having a good time already ok we got '\n",
+ " 'to talk some tea right now which is '\n",
+ " 'we saw the posters there was an '\n",
+ " 'outcry what was it like for you it '\n",
+ " 'was it was surprising I saw '\n",
+ " 'everybody in like you know the '\n",
+ " 'coloured photos in her coloured '\n",
+ " \"posters and then it's all my stuff \"\n",
+ " 'in grey and I was like you I just '\n",
+ " 'died'},\n",
+ " { 'transcript': \"oh my gosh Shirley is here but it's \"\n",
+ " 'alright how are you doing this '\n",
+ " \"evening very well I'm coming here I \"\n",
+ " \"don't know what to expect but I'm \"\n",
+ " 'having a good time already ok we '\n",
+ " 'have to talk some tea right now '\n",
+ " 'which is we saw the posters there '\n",
+ " 'was an outcry what was it like for '\n",
+ " 'you it was it was surprising I saw '\n",
+ " 'everybody in like you know the '\n",
+ " 'coloured photos in a coloured '\n",
+ " 'posters and myself in grey and I was '\n",
+ " 'like you I just died'},\n",
+ " { 'transcript': \"oh my gosh Shirley is here but it's \"\n",
+ " 'alright how are you doing this '\n",
+ " \"evening very well I'm coming here I \"\n",
+ " \"don't know what to expect but I'm \"\n",
+ " 'having a good time already ok we got '\n",
+ " 'to talk some tea right now which is '\n",
+ " 'we saw the posters there was an '\n",
+ " 'outcry what was it like for you it '\n",
+ " 'was it was surprising I saw '\n",
+ " 'everybody in like you know the '\n",
+ " 'coloured photos in a coloured '\n",
+ " \"posters and then it's all my stuff \"\n",
+ " 'in grey and I was like you I just '\n",
+ " 'died'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.95060402,\n",
+ " 'transcript': 'I just died out of nowhere and I '\n",
+ " 'think the whole of Twitter was '\n",
+ " 'really upset so I cannot log off and '\n",
+ " 'then log back on some waiting to see '\n",
+ " 'how that came together and have that '\n",
+ " 'planned out tonight thank you'},\n",
+ " { 'transcript': 'I just died out of nowhere and I '\n",
+ " 'think the whole of Twitter was '\n",
+ " 'really upset so I cannot log off and '\n",
+ " 'then log back on some waiting to see '\n",
+ " 'how that came together and have that '\n",
+ " 'kind out tonight we love you thank '\n",
+ " 'you'},\n",
+ " { 'transcript': 'I just died out of nowhere and I '\n",
+ " 'think the whole of Twitter was '\n",
+ " 'really upset so I cannot log off and '\n",
+ " 'then log back on some waiting to see '\n",
+ " 'how that came together and have that '\n",
+ " 'kind out tonight thank you'},\n",
+ " { 'transcript': 'I just died out of nowhere and I '\n",
+ " 'think the whole of Twitter was '\n",
+ " 'really upset so I cannot log off and '\n",
+ " 'then log back on some waiting to see '\n",
+ " 'how that came together and have that '\n",
+ " 'kind out tonight love you thank you'},\n",
+ " { 'transcript': 'I just died out of nowhere and I '\n",
+ " 'think the whole of Twitter was '\n",
+ " 'really upset so I cannot log off and '\n",
+ " 'then log back on some waiting to see '\n",
+ " 'how that came together and how that '\n",
+ " 'planned out tonight thank you'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.93798029,\n",
+ " 'transcript': \"surprised to know that you're even \"\n",
+ " \"though it wasn't top the other black \"\n",
+ " 'panther to be one of the favourite '\n",
+ " 'coming at the other end of the film'},\n",
+ " { 'transcript': \"surprised to know that you're even \"\n",
+ " \"though it wasn't top the other black \"\n",
+ " 'panther to be one of the favourite '\n",
+ " 'coming out the other end of the '\n",
+ " 'film'},\n",
+ " { 'transcript': \"surprised to know that you're even \"\n",
+ " \"though it wasn't top the other black \"\n",
+ " 'panther to be one of the fibres '\n",
+ " 'coming out the other end of the '\n",
+ " 'film'},\n",
+ " { 'transcript': \"surprised to know that you're even \"\n",
+ " \"though it wasn't top the other black \"\n",
+ " 'panther to be one of the favourites '\n",
+ " 'coming at the other end of the film'},\n",
+ " { 'transcript': \"surprised to know that you're even \"\n",
+ " \"though I wasn't top the other black \"\n",
+ " 'panther to be one of the favourite '\n",
+ " 'coming at the other end of the '\n",
+ " 'film'}],\n",
+ " 'final': True}\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92333227,\n",
+ " 'transcript': 'is coming up the major surprise one '\n",
+ " 'that I thank God for his just I want '\n",
+ " 'to set everyday wanting to give my '\n",
+ " 'best ones in to work hard and to see '\n",
+ " 'that'},\n",
+ " { 'transcript': 'what is coming up the major surprise '\n",
+ " 'one that I thank God for his just I '\n",
+ " 'want to set everyday wanting to give '\n",
+ " 'my best ones in to work hard and to '\n",
+ " 'see that'},\n",
+ " { 'transcript': 'is coming up the major surprise one '\n",
+ " 'that I thank God for his just I went '\n",
+ " 'to set everyday wanting to give my '\n",
+ " 'best ones into work hard and to see '\n",
+ " 'that'},\n",
+ " { 'transcript': 'what is coming up to the major '\n",
+ " 'surprise one that I thank God for '\n",
+ " 'his just I want to set everyday '\n",
+ " 'wanting to give my best ones in to '\n",
+ " 'work hard and to see that'},\n",
+ " { 'transcript': 'is coming up to the major surprise '\n",
+ " 'one that I thank God for his just I '\n",
+ " 'want to set everyday wanting to give '\n",
+ " 'my best ones in to work hard and to '\n",
+ " 'see that'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.92210746,\n",
+ " 'transcript': 'see that that result in that love '\n",
+ " \"you know I didn't expect it\"},\n",
+ " { 'transcript': 'see that that result in that love '\n",
+ " \"you no I didn't expect it\"},\n",
+ " { 'transcript': 'I see that that result in that love '\n",
+ " \"you know I didn't expect it\"},\n",
+ " { 'transcript': 'I see that that result in that love '\n",
+ " \"you no I didn't expect it\"},\n",
+ " { 'transcript': 'see that that result in that loves '\n",
+ " \"you know I didn't expect it\"}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.95232391,\n",
+ " 'transcript': 'expect it but I thank God for it and '\n",
+ " 'now I feel a part of the family so '\n",
+ " \"hopefully you know if I don't do \"\n",
+ " 'this film I want to see what happens '\n",
+ " 'I might not get some continue work '\n",
+ " \"let's see what happens well I do \"\n",
+ " 'know that I love seeing you get to '\n",
+ " 'team up with the Avengers infinity '\n",
+ " 'war and I love particularly when '\n",
+ " 'your school the boys the science '\n",
+ " 'Bros any chance that true would like '\n",
+ " 'to hang with those guys just in '\n",
+ " 'general really good but you know the '\n",
+ " \"way this film is set up we don't \"\n",
+ " \"know what's going to happen so let's \"\n",
+ " 'watch it'},\n",
+ " { 'transcript': 'expect it but I thank God for it and '\n",
+ " 'now I feel a part of the family so '\n",
+ " \"hopefully you know if I don't do \"\n",
+ " 'this film I want to see what happens '\n",
+ " 'I might not get some continue work '\n",
+ " \"let's see what happens well I do \"\n",
+ " 'know that I love seeing you get to '\n",
+ " 'team up with the Avengers infinity '\n",
+ " 'war and I love particularly when '\n",
+ " 'your school the boys the science '\n",
+ " 'Bros any chance that through would '\n",
+ " 'like to hang with those guys just in '\n",
+ " 'general really good but you know the '\n",
+ " \"way this film is set up we don't \"\n",
+ " \"know what's going to happen so let's \"\n",
+ " 'watch it'},\n",
+ " { 'transcript': 'expect it but I thank God for it and '\n",
+ " 'now I feel a part of the family so '\n",
+ " \"hopefully you'll know if I don't do \"\n",
+ " 'this film I want to see what happens '\n",
+ " 'I might not get some continue work '\n",
+ " \"let's see what happens well I do \"\n",
+ " 'know that I love seeing you get to '\n",
+ " 'team up with the Avengers infinity '\n",
+ " 'war and I love particularly when '\n",
+ " 'your school the boys the science '\n",
+ " 'Bros any chance that true would like '\n",
+ " 'to hang with those guys just in '\n",
+ " 'general really good but you know the '\n",
+ " \"way this film is set up we don't \"\n",
+ " \"know what's going to happen so let's \"\n",
+ " 'watch it'},\n",
+ " { 'transcript': 'expect it but thank god for it and '\n",
+ " 'now I feel a part of the family so '\n",
+ " \"hopefully you know if I don't do \"\n",
+ " 'this film I want to see what happens '\n",
+ " 'I might not get some continue work '\n",
+ " \"let's see what happens well I do \"\n",
+ " 'know that I love seeing you get to '\n",
+ " 'team up with the Avengers infinity '\n",
+ " 'war and I love particularly when '\n",
+ " 'your school the boys the science '\n",
+ " 'Bros any chance that true would like '\n",
+ " 'to hang with those guys just in '\n",
+ " 'general really good but you know the '\n",
+ " \"way this film is set up we don't \"\n",
+ " \"know what's going to happen so let's \"\n",
+ " 'watch it'},\n",
+ " { 'transcript': 'expect it but thank god for it and '\n",
+ " 'now I feel a part of the family so '\n",
+ " \"hopefully you know if I don't do \"\n",
+ " 'this film I want to see what happens '\n",
+ " 'I might not get some continue work '\n",
+ " \"let's see what happens well I do \"\n",
+ " 'know that I love seeing you get to '\n",
+ " 'team up with the Avengers infinity '\n",
+ " 'war and I love particularly when '\n",
+ " 'your school the boys the science '\n",
+ " 'Bros any chance that through would '\n",
+ " 'like to hang with those guys just in '\n",
+ " 'general really good but you know the '\n",
+ " \"way this film is set up we don't \"\n",
+ " \"know what's going to happen so let's \"\n",
+ " 'watch it'}],\n",
+ " 'final': True}\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.91882193,\n",
+ " 'transcript': 'it was only 6'},\n",
+ " {'transcript': 'it was only six'},\n",
+ " {'transcript': 'it was only fix'},\n",
+ " {'transcript': 'it was only folks'},\n",
+ " {'transcript': 'it was only fixed'}],\n",
+ " 'final': True}\n",
+ "result2:\n",
+ "{ 'alternative': [ { 'confidence': 0.94119203,\n",
+ " 'transcript': '6 fingers crossed and see what the '\n",
+ " 'Russo Brothers looked up for us and '\n",
+ " 'yeah hopefully hopefully in the '\n",
+ " 'future we can sit down with these '\n",
+ " 'guys you know'},\n",
+ " { 'transcript': 'six fingers crossed and see what the '\n",
+ " 'Russo Brothers looked up for us and '\n",
+ " 'yeah hopefully hopefully in the '\n",
+ " 'future we can sit down with these '\n",
+ " 'guys you know'},\n",
+ " { 'transcript': '6 fingers crossed and see what the '\n",
+ " 'Russo Brothers have cooked up for us '\n",
+ " 'and yeah hopefully hopefully in the '\n",
+ " 'future we can sit down with these '\n",
+ " 'guys you know'},\n",
+ " { 'transcript': 'six fingers crossed and see what the '\n",
+ " 'Russo brothers are cooked up for us '\n",
+ " 'and yeah hopefully hopefully in the '\n",
+ " 'future we can sit down with these '\n",
+ " 'guys you know'},\n",
+ " { 'transcript': '6 fingers crossed and see what the '\n",
+ " 'Russo Brothers looked up for us and '\n",
+ " 'yeah hopefully will be in the future '\n",
+ " 'we can sit down with these guys you '\n",
+ " 'know'}],\n",
+ " 'final': True}\n"
+ ]
+ }
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+ "ap_en = AudioProcessor(configuration_en, audio_path_en)\n",
+ "t1 = time.time()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "id": "4afd78f3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'Execution time : 33.121073722839355 seconds.'"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\"Execution time : {} seconds.\".format(t1-t0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "594f6020",
+ "metadata": {},
+ "outputs": [
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+ "\n",
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+ "0 oh my gosh she is here but it's alright how are you doing this evening very well I'm coming here I don't know what to expect but I'm having a good time already ok we have to talk some tea right now which is we saw the posters there was an outcry what was it like for you it was it was surprising I saw everybody in like you know the coloured photos in a coloured posters and then it's all my stuff in grey and I was like you I just died \n",
+ "1 I just died out of nowhere and I think the whole of Twitter was really upset so I cannot log off and then log back on some waiting to see how that came together and have that planned out tonight thank you \n",
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+ "5 expect it but I thank God for it and now I feel a part of the family so hopefully you know if I don't do this film I want to see what happens I might not get some continue work let's see what happens well I do know that I love seeing you get to team up with the Avengers infinity war and I love particularly when your school the boys the science Bros any chance that true would like to hang with those guys just in general really good but you know the way this film is set up we don't know what's going to happen so let's watch it \n",
+ "6 it was only 6 \n",
+ "7 6 fingers crossed and see what the Russo Brothers looked up for us and yeah hopefully hopefully in the future we can sit down with these guys you know "
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
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+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9bf50120",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
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+ "name": "python3"
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