audiosplit.py

# -*- coding:utf-8 -*-
import collections
import contextlib
import sys
import wave # It has been modified and put into the same directory as this file
import os
import webrtcvad
import soundfile
import argparse
import functools
from utils.utility import add_arguments

import sys
reload(sys)
sys.setdefaultencoding("utf-8")


parser = argparse.ArgumentParser(description=__doc__)
add_arg = functools.partial(add_arguments, argparser=parser)
add_arg('target_dir',       str,    '',     "# of audios to split.")
add_arg('output_dir',	    str,    '', '# path t result')
args = parser.parse_args()
def read_wave(path):
    """Reads a .wav file.

    Takes the path, and returns (PCM audio data, sample rate).
    """
    with contextlib.closing(wave.open(path, 'rb')) as wf:
        num_channels = wf.getnchannels()
        assert num_channels == 1
        sample_width = wf.getsampwidth()
        assert sample_width == 2
        sample_rate = wf.getframerate()
        assert sample_rate in (8000, 16000, 32000, 48000)
        pcm_data = wf.readframes(wf.getnframes())
        return pcm_data, sample_rate


def write_wave(path, audio, sample_rate):
    """Writes a .wav file.

    Takes path, PCM audio data, and sample rate.
    """
    with contextlib.closing(wave.open(path, 'wb')) as wf:
        wf.setnchannels(1)
        wf.setsampwidth(2)
        wf.setframerate(sample_rate)
        wf.writeframes(audio)


class Frame(object):
    """Represents a "frame" of audio data."""
    def __init__(self, bytes, timestamp, duration):
        self.bytes = bytes
        self.timestamp = timestamp
        self.duration = duration


def frame_generator(frame_duration_ms, audio, sample_rate):
    """Generates audio frames from PCM audio data.

    Takes the desired frame duration in milliseconds, the PCM data, and
    the sample rate.

    Yields Frames of the requested duration.
    """
    n = int(sample_rate * (frame_duration_ms / 1000.0) * 2)
    offset = 0
    timestamp = 0.0
    duration = (float(n) / sample_rate) / 2.0
    while offset + n < len(audio):
        yield Frame(audio[offset:offset + n], timestamp, duration)
        timestamp += duration
        offset += n


def vad_collector(sample_rate, frame_duration_ms,
                  padding_duration_ms, vad, frames):
    """Filters out non-voiced audio frames.

    Given a webrtcvad.Vad and a source of audio frames, yields only
    the voiced audio.

    Uses a padded, sliding window algorithm over the audio frames.
    When more than 90% of the frames in the window are voiced (as
    reported by the VAD), the collector triggers and begins yielding
    audio frames. Then the collector waits until 90% of the frames in
    the window are unvoiced to detrigger.

    The window is padded at the front and back to provide a small
    amount of silence or the beginnings/endings of speech around the
    voiced frames.

    Arguments:

    sample_rate - The audio sample rate, in Hz.
    frame_duration_ms - The frame duration in milliseconds.
    padding_duration_ms - The amount to pad the window, in milliseconds.
    vad - An instance of webrtcvad.Vad.
    frames - a source of audio frames (sequence or generator).

    Returns: A generator that yields PCM audio data.
    """
    num_padding_frames = int(padding_duration_ms / frame_duration_ms)
    # We use a deque for our sliding window/ring buffer.
    ring_buffer = collections.deque(maxlen=num_padding_frames)
    # We have two states: TRIGGERED and NOTTRIGGERED. We start in the
    # NOTTRIGGERED state.
    triggered = False

    voiced_frames = []
    for frame in frames:
        is_speech = vad.is_speech(frame.bytes, sample_rate)

        sys.stdout.write('1' if is_speech else '0')
        if not triggered:
            ring_buffer.append((frame, is_speech))
            num_voiced = len([f for f, speech in ring_buffer if speech])
            # If we're NOTTRIGGERED and more than 90% of the frames in
            # the ring buffer are voiced frames, then enter the
            # TRIGGERED state.
            if num_voiced > 0.9 * ring_buffer.maxlen:
                triggered = True
                sys.stdout.write('+(%s)' % (ring_buffer[0][0].timestamp,))
                # We want to yield all the audio we see from now until
                # we are NOTTRIGGERED, but we have to start with the
                # audio that's already in the ring buffer.
                for f, s in ring_buffer:
                    voiced_frames.append(f)
                ring_buffer.clear()
        else:
            # We're in the TRIGGERED state, so collect the audio data
            # and add it to the ring buffer.
            voiced_frames.append(frame)
            ring_buffer.append((frame, is_speech))
            num_unvoiced = len([f for f, speech in ring_buffer if not speech])
            # If more than 90% of the frames in the ring buffer are
            # unvoiced, then enter NOTTRIGGERED and yield whatever
            # audio we've collected.
            if num_unvoiced > 0.9 * ring_buffer.maxlen:
                sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration))
                triggered = False
                yield b''.join([f.bytes for f in voiced_frames])
                ring_buffer.clear()
                voiced_frames = []
    if triggered:
        sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration))
    sys.stdout.write('\n')
    # If we have any leftover voiced audio when we run out of input,
    # yield it.
    if voiced_frames:
        yield b''.join([f.bytes for f in voiced_frames])


def extract_name(directory):
    """
    extract the audio's filename from a directory
    """
    if '/' not in directory:
        return directory[:-4]
    
    return directory.split('/')[-1][:-4]
    
    

def main():
    
    if(args.target_dir[-3:]=='wav'):
    	audio, sample_rate = read_wave(args.target_dir)
    	vad = webrtcvad.Vad(2)
    	frames = frame_generator(30,audio,sample_rate)
    	frames = list(frames)
    	segments = vad_collector(sample_rate, 30, 500, vad, frames)
    	for i, segment in enumerate(segments):
        	path = args.output_dir+'/'+ extract_name(args.target_dir)+'-%002d.wav' % (i,)
        	print(' Writing %s' % (path,))
        	write_wave(path, segment, sample_rate)
    else:
	padding_duration = 450
	while padding_duration >= 200:
            for subfolder,_,filelist in sorted(os.walk(args.target_dir)):
                for fname in sorted(filelist):
		    if(fname[-3:]=='wav'):
                        audio_path =os.path.join(subfolder, fname)
                        audio,sample_rate = read_wave(audio_path)
                        duration = float(len(audio) / sample_rate)
                        if(duration > 30):
                            vad = webrtcvad.Vad(2)
                            frames = frame_generator(30, audio, sample_rate)
                            frames =list(frames)
                            segments = vad_collector(sample_rate, 30, padding_duration, vad, frames)
                            for i, segment in enumerate(segments):
                               path = args.output_dir+'/'+fname[:-4]+'-%002d.wav' %(i,)
                               print('Writing %s' %(path,))
                               write_wave(path,segment,sample_rate)
		            os.remove(audio_path)
		padding_duration -= 50

if __name__ == '__main__':
    main()