openAI_whisper_convert_audio_to_txt.ipynb

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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VU8cgD048L37",
        "outputId": "dbd314cf-d2b9-4c5a-81fb-cf68badd32c4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/openai/whisper.git\n",
            "  Cloning https://github.com/openai/whisper.git to /tmp/pip-req-build-8k0y4pul\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/openai/whisper.git /tmp/pip-req-build-8k0y4pul\n",
            "  Resolved https://github.com/openai/whisper.git to commit e8622f9afc4eba139bf796c210f5c01081000472\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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            "Building wheels for collected packages: openai-whisper\n",
            "  Building wheel for openai-whisper (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for openai-whisper: filename=openai_whisper-20230314-py3-none-any.whl size=798395 sha256=b30178aa95038cd01e02c98f9eecf1af27e65c3ef96b7a8a63731d6ae36fe367\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-en664r8n/wheels/8b/6c/d0/622666868c179f156cf595c8b6f06f88bc5d80c4b31dccaa03\n",
            "Successfully built openai-whisper\n",
            "Installing collected packages: tiktoken, openai-whisper\n",
            "Successfully installed openai-whisper-20230314 tiktoken-0.3.3\n",
            "Get:1 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,626 B]\n",
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            "Fetched 10.6 MB in 7s (1,453 kB/s)\n",
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "19 packages can be upgraded. Run 'apt list --upgradable' to see them.\n",
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "ffmpeg is already the newest version (7:4.4.2-0ubuntu0.22.04.1).\n",
            "0 upgraded, 0 newly installed, 0 to remove and 19 not upgraded.\n"
          ]
        }
      ],
      "source": [
        " !pip install git+https://github.com/openai/whisper.git #install whisper getting from github\n",
        " !sudo apt update && sudo apt install ffmpeg #ffmpeg allows us to work with audio and video files"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install pytube"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EOSaMQg9-wrz",
        "outputId": "75ee81dc-74fa-4a0f-87a2-98a97497ded5"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pytube\n",
            "  Downloading pytube-15.0.0-py3-none-any.whl (57 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/57.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.6/57.6 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: pytube\n",
            "Successfully installed pytube-15.0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pytube import YouTube\n",
        "\n",
        "def download_youtube_audio(video_url):\n",
        "    yt = YouTube(video_url)\n",
        "    stream = yt.streams.filter(only_audio=True).first()\n",
        "    audio_file_path = yt.title + \".mp3\"  # Output audio file path\n",
        "\n",
        "    stream.download(filename=audio_file_path)\n",
        "\n",
        "    return audio_file_path\n",
        "\n",
        "# Main code flow\n",
        "video_url = \"https://www.youtube.com/watch?v=vWh1AJwAIg0\"\n",
        "audio_file_path = download_youtube_audio(video_url)"
      ],
      "metadata": {
        "id": "3JIf40aj8jPC"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can choose 5 different model:\n",
        "\n",
        "\n",
        "*   Tiny\n",
        "*   Base\n",
        "*   Small\n",
        "*   Medium\n",
        "*   Large\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "eARsDWJ6_WsD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        " # run whisper asr\n",
        " !whisper \"/content/Pharmacology - IMMUNOSUPPRESSANTS (MADE EASY).mp3\" --model medium.en"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9XOOJxFj-zKR",
        "outputId": "a4d52b6a-609d-4580-b90e-5b20ae87d923"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "100%|██████████████████████████████████████| 1.42G/1.42G [00:14<00:00, 104MiB/s]\n",
            "[00:00.000 --> 00:08.100]  In this lecture we are gonna cover the pharmacology of immunosuppressants, so let's get right\n",
            "[00:08.100 --> 00:09.400]  into it.\n",
            "[00:09.400 --> 00:14.000]  The immune system is a complex network of cells and proteins that work together to defend\n",
            "[00:14.000 --> 00:18.720]  the body against substances it sees as harmful or foreign.\n",
            "[00:18.720 --> 00:23.840]  Now the human immune system has two levels of immunity, innate and adaptive.\n",
            "[00:23.840 --> 00:29.500]  The innate immunity is nonspecific and fast-acting, and serves as the primary line of protection\n",
            "[00:29.500 --> 00:31.980]  against pathogen invasion.\n",
            "[00:31.980 --> 00:36.620]  Numerous cells are involved in the innate immune response, including natural killer\n",
            "[00:36.620 --> 00:42.580]  cells, mast cells and granulocytes, as well as the phagocytic cells such as macrophages,\n",
            "[00:42.580 --> 00:48.140]  dendritic cells and monocytes, that utilize phagocytosis and are equipped with receptors\n",
            "[00:48.140 --> 00:53.760]  which recognize a variety of microbial products known as antigens, resulting in activation\n",
            "[00:53.760 --> 00:59.000]  of the slower-acting, but more specific, adaptive immune system.\n",
            "[00:59.000 --> 01:03.920]  Now the adaptive immune system consists of highly specialized systemic cells and processes\n",
            "[01:03.920 --> 01:09.100]  that are separated into two main components, the humoral and cellular.\n",
            "[01:09.100 --> 01:14.520]  The humoral immunity is mediated by activated B cells that produce and secrete antibodies\n",
            "[01:14.520 --> 01:17.120]  against a specific antigen.\n",
            "[01:17.120 --> 01:23.340]  On the other hand, the cellular immunity is mediated by T lymphocytes, also called T cells.\n",
            "[01:23.340 --> 01:27.600]  Now T cells circulate throughout the body until they recognize a specific antigen they\n",
            "[01:27.600 --> 01:33.380]  are programmed for, on the surface of antigen-presenting cells, such as dendritic cells.\n",
            "[01:33.380 --> 01:40.020]  The T cell receptor on both CD4-positive helper T cells and CD8-positive cytotoxic T cells\n",
            "[01:40.020 --> 01:45.820]  binds to the antigen as it is held in a structure called the Major Histocompatibility Complex\n",
            "[01:45.820 --> 01:52.340]  – MHC for short – in order to discriminate for and from self-antigens and initiate adaptive\n",
            "[01:52.340 --> 01:54.620]  immune responses.\n",
            "[01:54.640 --> 02:00.560]  This sets off a signaling cascade that allows T cells to replicate, differentiate, and secrete\n",
            "[02:00.560 --> 02:05.240]  signaling proteins called cytokines, which in turn activate more cells of the immune\n",
            "[02:05.240 --> 02:07.080]  system.\n",
            "[02:07.080 --> 02:12.640]  Now depending on the type of T cell, either the core receptor CD8 or CD4 binds to the\n",
            "[02:12.640 --> 02:14.200]  MHC molecule.\n",
            "[02:14.200 --> 02:19.280]  The signal transduction is then carried through CD3 that is physically associated with a T\n",
            "[02:19.280 --> 02:20.800]  cell receptor.\n",
            "[02:20.800 --> 02:26.060]  However this initial signal is not sufficient for T cell activation, therefore a secondary\n",
            "[02:26.060 --> 02:28.300]  signal is required.\n",
            "[02:28.300 --> 02:34.040]  This secondary signal, also referred to as costimulation, occurs when CD28 receptor expressed\n",
            "[02:34.040 --> 02:41.100]  on T cells binds CD80 and CD86 molecules that are expressed on antigen-presenting cells,\n",
            "[02:41.100 --> 02:45.900]  thereby triggering a calcium-mediated signaling cascade.\n",
            "[02:45.900 --> 02:51.120]  Basically a rise in intracellular calcium levels leads to a stepwise activation of the\n",
            "[02:51.120 --> 02:57.120]  phosphatase calcine urine, an enzyme that dephosphorylates nuclear factor of activated\n",
            "[02:57.120 --> 03:02.740]  T cells – NFAT for short – which in turn allows it to translocate from the cytoplasm\n",
            "[03:02.740 --> 03:05.680]  into the nucleus.\n",
            "[03:05.680 --> 03:11.080]  Inside the nucleus, NFAT proteins bind DNA target sequences in cooperation with partnering\n",
            "[03:11.080 --> 03:16.980]  transcription factors, leading to activation of genes encoding cytokines, one of which\n",
            "[03:16.980 --> 03:22.740]  is a major growth factor called interleukin-2, IL-2 for short.\n",
            "[03:22.740 --> 03:28.900]  Now generated interleukin-2 binds to the interleukin-2 receptors on the surface of T cells activating\n",
            "[03:28.900 --> 03:34.780]  a signaling protein called a mammalian target of rapamycin, mTOR for short, thereby allowing\n",
            "[03:34.780 --> 03:39.820]  the cell to progress through the cell cycle, promoting cell proliferation of antigen-prime\n",
            "[03:39.840 --> 03:46.600]  T cells, which subsequently produce more interleukin-2, as well as other pro-inflammatory cytokines\n",
            "[03:46.600 --> 03:52.040]  activating natural killer cells, macrophages, and cytotoxic T cells.\n",
            "[03:52.040 --> 03:57.720]  Alright, so the immune system is critical to survival in an environment full of pathogenic\n",
            "[03:57.720 --> 03:58.720]  microbes.\n",
            "[03:58.720 --> 04:04.760]  However, this vital system is not always protective, as deregulation of immune responses can lead\n",
            "[04:04.760 --> 04:09.500]  to chronic inflammatory diseases such as autoimmunity or cancer.\n",
            "[04:09.500 --> 04:14.620]  Moreover, the immune system serves as a barrier for the transplantation of certain beneficial\n",
            "[04:14.620 --> 04:16.180]  organs and tissues.\n",
            "[04:16.180 --> 04:21.820]  Therefore, a continuous use of immunosuppressive drugs is the standard of care for managing\n",
            "[04:21.820 --> 04:25.380]  autoimmunity and transplant rejection.\n",
            "[04:25.380 --> 04:29.380]  Now immunosuppressive drug therapy usually consists of two or more agents with different\n",
            "[04:29.380 --> 04:34.240]  mechanisms of action that disrupt various levels of T cell activation.\n",
            "[04:34.240 --> 04:39.220]  So let's discuss these one by one, starting with calcine urine inhibitors.\n",
            "[04:39.220 --> 04:44.780]  Drugs in this group work by binding to intracellular proteins called immunophilins.\n",
            "[04:44.780 --> 04:50.300]  Immunophilins consist of two protein families, known as cyclophilins and FK-binding proteins,\n",
            "[04:50.300 --> 04:57.400]  and are the major receptors for the immunosuppressive drugs cyclosporine and tacrolimus, respectively.\n",
            "[04:57.400 --> 05:02.420]  These complexes then bind to and inhibit calcine urine, thereby preventing nuclear factor of\n",
            "[05:02.420 --> 05:07.680]  activated T cells from moving to the nucleus, which ultimately impairs transcription of\n",
            "[05:07.680 --> 05:13.200]  the genes encoding interleukin-2 that is necessary for activation of T cells.\n",
            "[05:13.200 --> 05:19.640]  Alright, moving on to the next group of immunosuppressants, that is costimulation blockers.\n",
            "[05:19.640 --> 05:25.120]  Drugs in this group include belatacept and abatacept, which work by selectively binding\n",
            "[05:25.120 --> 05:32.000]  to CD80 and CD86 on antigen-presenting cells, thereby blocking interaction with CD28 on\n",
            "[05:32.000 --> 05:33.660]  T cells.\n",
            "[05:33.660 --> 05:39.940]  This in turn prevents complete T cell activation, reduces T cell proliferation and interleukin-2\n",
            "[05:39.940 --> 05:41.360]  production.\n",
            "[05:41.360 --> 05:45.480]  That being said, it's important to remember here that belatacept was designed to bind\n",
            "[05:45.480 --> 05:52.060]  to CD80 and CD86 more strongly than abatacept and thus has been shown to be more effective\n",
            "[05:52.060 --> 05:56.340]  in the immunosuppression necessary for transplant rejection.\n",
            "[05:56.340 --> 06:01.780]  Now moving on to our third group of immunosuppressants, that is mTOR inhibitors.\n",
            "[06:01.780 --> 06:07.820]  Drugs in this group include sirolimus, also known as rapamycin, and everolimus, which\n",
            "[06:07.820 --> 06:13.480]  work by binding to the same intracellular FK-binding protein as tacrolimus, however\n",
            "[06:13.480 --> 06:19.400]  instead of forming a complex with calcine urine, sirolimus and everolimus subsequently\n",
            "[06:19.400 --> 06:23.360]  bind to mTOR, thereby inhibiting its activity.\n",
            "[06:23.360 --> 06:28.280]  This ultimately leads to slowing or arrest of cell cycle progression, as well as inhibition\n",
            "[06:28.280 --> 06:32.260]  of the cellular response to interleukin-2.\n",
            "[06:32.260 --> 06:37.180]  Alright moving on to the next class of drugs that is immunosuppressive antimetabolites.\n",
            "[06:37.180 --> 06:42.960]  The two most commonly used agents in this class are azathioprine and mycophenolate mofetil,\n",
            "[06:42.960 --> 06:46.280]  which have similar but unique mechanism of action.\n",
            "[06:46.280 --> 06:52.760]  So the first one azathioprine is first activated to become 6 mercapto purine, 6MP for short,\n",
            "[06:52.760 --> 06:57.260]  which is then further metabolized to form purine analogs that mimic the structure of\n",
            "[06:57.260 --> 06:59.720]  a building block of DNA.\n",
            "[06:59.720 --> 07:04.680]  These false purines in turn can disrupt the novel pathway of purine synthesis, as well\n",
            "[07:04.680 --> 07:10.600]  as become incorporated into DNA and RNA, thus terminating their synthesis, ultimately inhibiting\n",
            "[07:10.600 --> 07:13.640]  cellular proliferation.\n",
            "[07:13.640 --> 07:19.720]  Now in contrast, the second agent, mycophenolate mofetil, works by inhibiting inosine monophosphate\n",
            "[07:19.720 --> 07:25.920]  dehydrogenase, IMPDH for short, a key enzyme in purine synthesis, which is involved in\n",
            "[07:25.920 --> 07:28.820]  the production of guanosine nucleotides.\n",
            "[07:28.820 --> 07:33.960]  As a result, DNA synthesis, which requires guanosine triphosphate, does not occur and\n",
            "[07:33.960 --> 07:36.060]  cell proliferation is inhibited.\n",
            "[07:36.060 --> 07:42.120]  However, unlike azathioprine, mycophenolate is not incorporated into DNA and does not\n",
            "[07:42.120 --> 07:45.180]  induce chromosome breaks.\n",
            "[07:45.180 --> 07:49.840]  Now another class of drugs that is often used for immunosuppression in both transplantation\n",
            "[07:49.840 --> 07:53.920]  and various autoimmune disorders is corticosteroids.\n",
            "[07:53.920 --> 07:59.620]  Drugs that belong to this class include prednisone, prednisolone, and methylprednisolone.\n",
            "[07:59.620 --> 08:05.180]  So the effects of corticosteroids are diverse and are likely controlled by several mechanisms.\n",
            "[08:05.180 --> 08:09.620]  One mechanism by which corticosteroids induce immunosuppression is through regulation of\n",
            "[08:09.620 --> 08:11.980]  the T-cell responses.\n",
            "[08:11.980 --> 08:17.200]  Acting directly on T-cells, corticosteroids mediate their effects by binding to the intracellular\n",
            "[08:17.200 --> 08:22.740]  glucocorticoid receptor, resulting in translocation of the complex to the nucleus and subsequent\n",
            "[08:22.740 --> 08:28.580]  inhibition of key transcription factors, such as nuclear factor kappaB and activator\n",
            "[08:28.580 --> 08:35.860]  protein 1, which ultimately alters gene transcription and represses pro-inflammatory genes.\n",
            "[08:35.860 --> 08:41.300]  In addition to this, corticosteroids exert non-genomic actions by causing rapid dissociation\n",
            "[08:41.300 --> 08:47.660]  of a T-cell receptor-associated protein complexes, resulting in impaired receptor signaling and\n",
            "[08:47.660 --> 08:49.460]  T-cell activation.\n",
            "[08:49.460 --> 08:55.260]  Finally, moving on to our last class of immunosuppressants, that is, antibodies.\n",
            "[08:55.260 --> 08:59.340]  Now although many different antibody products exist, for the purpose of this lecture we\n",
            "[08:59.340 --> 09:03.260]  are gonna focus here only on the two that are most commonly used to prevent transplant\n",
            "[09:03.260 --> 09:04.820]  rejection.\n",
            "[09:04.820 --> 09:10.820]  The first such product is anti-timocyte globulins, which consists of polyclonal antibodies that\n",
            "[09:10.820 --> 09:15.660]  bind to a wide variety of proteins on the surface of T-cells, leading to cell death\n",
            "[09:15.660 --> 09:20.420]  via complement-mediated cytotoxicity or apoptosis.\n",
            "[09:20.420 --> 09:26.020]  The second antibody product commonly used in transplant is basiliximab, which is a monoclonal\n",
            "[09:26.020 --> 09:32.160]  antibody that binds to interleukin-2 receptor with similar affinity as interleukin-2, thereby\n",
            "[09:32.160 --> 09:37.660]  effectively competing with interleukin-2 and subsequently inhibiting interleukin-2-driven\n",
            "[09:37.660 --> 09:40.780]  T-cell proliferation.\n",
            "[09:40.780 --> 09:45.340]  And with that I wanted to thank you for watching, I hope you enjoyed this video, and as always\n",
            "[09:45.340 --> 09:46.300]  stay tuned for more!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "you should see an SRT file, a TXT file and a VTT file. A text file is just all of the text from the audio. SRT and VTT these are caption formats that also include timestamps"
      ],
      "metadata": {
        "id": "lOKKYn1rAKo0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        " #additional arguments\n",
        " !whisper -h"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "282lOJLFCmgM",
        "outputId": "2b7ee008-67c1-48c6-da1c-dac0dc9ba6ae"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "usage: whisper\n",
            "       [-h]\n",
            "       [--model {tiny.en,tiny,base.en,base,small.en,small,medium.en,medium,large-v1,large-v2,large}]\n",
            "       [--model_dir MODEL_DIR]\n",
            "       [--device DEVICE]\n",
            "       [--output_dir OUTPUT_DIR]\n",
            "       [--output_format {txt,vtt,srt,tsv,json,all}]\n",
            "       [--verbose VERBOSE]\n",
            "       [--task {transcribe,translate}]\n",
            "       [--language {af,am,ar,as,az,ba,be,bg,bn,bo,br,bs,ca,cs,cy,da,de,el,en,es,et,eu,fa,fi,fo,fr,gl,gu,ha,haw,he,hi,hr,ht,hu,hy,id,is,it,ja,jw,ka,kk,km,kn,ko,la,lb,ln,lo,lt,lv,mg,mi,mk,ml,mn,mr,ms,mt,my,ne,nl,nn,no,oc,pa,pl,ps,pt,ro,ru,sa,sd,si,sk,sl,sn,so,sq,sr,su,sv,sw,ta,te,tg,th,tk,tl,tr,tt,uk,ur,uz,vi,yi,yo,zh,Afrikaans,Albanian,Amharic,Arabic,Armenian,Assamese,Azerbaijani,Bashkir,Basque,Belarusian,Bengali,Bosnian,Breton,Bulgarian,Burmese,Castilian,Catalan,Chinese,Croatian,Czech,Danish,Dutch,English,Estonian,Faroese,Finnish,Flemish,French,Galician,Georgian,German,Greek,Gujarati,Haitian,Haitian Creole,Hausa,Hawaiian,Hebrew,Hindi,Hungarian,Icelandic,Indonesian,Italian,Japanese,Javanese,Kannada,Kazakh,Khmer,Korean,Lao,Latin,Latvian,Letzeburgesch,Lingala,Lithuanian,Luxembourgish,Macedonian,Malagasy,Malay,Malayalam,Maltese,Maori,Marathi,Moldavian,Moldovan,Mongolian,Myanmar,Nepali,Norwegian,Nynorsk,Occitan,Panjabi,Pashto,Persian,Polish,Portuguese,Punjabi,Pushto,Romanian,Russian,Sanskrit,Serbian,Shona,Sindhi,Sinhala,Sinhalese,Slovak,Slovenian,Somali,Spanish,Sundanese,Swahili,Swedish,Tagalog,Tajik,Tamil,Tatar,Telugu,Thai,Tibetan,Turkish,Turkmen,Ukrainian,Urdu,Uzbek,Valencian,Vietnamese,Welsh,Yiddish,Yoruba}]\n",
            "       [--temperature TEMPERATURE]\n",
            "       [--best_of BEST_OF]\n",
            "       [--beam_size BEAM_SIZE]\n",
            "       [--patience PATIENCE]\n",
            "       [--length_penalty LENGTH_PENALTY]\n",
            "       [--suppress_tokens SUPPRESS_TOKENS]\n",
            "       [--initial_prompt INITIAL_PROMPT]\n",
            "       [--condition_on_previous_text CONDITION_ON_PREVIOUS_TEXT]\n",
            "       [--fp16 FP16]\n",
            "       [--temperature_increment_on_fallback TEMPERATURE_INCREMENT_ON_FALLBACK]\n",
            "       [--compression_ratio_threshold COMPRESSION_RATIO_THRESHOLD]\n",
            "       [--logprob_threshold LOGPROB_THRESHOLD]\n",
            "       [--no_speech_threshold NO_SPEECH_THRESHOLD]\n",
            "       [--word_timestamps WORD_TIMESTAMPS]\n",
            "       [--prepend_punctuations PREPEND_PUNCTUATIONS]\n",
            "       [--append_punctuations APPEND_PUNCTUATIONS]\n",
            "       [--highlight_words HIGHLIGHT_WORDS]\n",
            "       [--max_line_width MAX_LINE_WIDTH]\n",
            "       [--max_line_count MAX_LINE_COUNT]\n",
            "       [--threads THREADS]\n",
            "       audio\n",
            "       [audio ...]\n",
            "\n",
            "positional arguments:\n",
            "  audio\n",
            "    audio\n",
            "    file(s) to\n",
            "    transcribe\n",
            "\n",
            "options:\n",
            "  -h, --help\n",
            "    show this\n",
            "    help\n",
            "    message and\n",
            "    exit\n",
            "  --model {tiny.en,tiny,base.en,base,small.en,small,medium.en,medium,large-v1,large-v2,large}\n",
            "    name of the\n",
            "    Whisper\n",
            "    model to\n",
            "    use\n",
            "    (default:\n",
            "    small)\n",
            "  --model_dir MODEL_DIR\n",
            "    the path to\n",
            "    save model\n",
            "    files; uses\n",
            "    ~/.cache/wh\n",
            "    isper by\n",
            "    default\n",
            "    (default:\n",
            "    None)\n",
            "  --device DEVICE\n",
            "    device to\n",
            "    use for\n",
            "    PyTorch\n",
            "    inference\n",
            "    (default:\n",
            "    cuda)\n",
            "  --output_dir OUTPUT_DIR, -o OUTPUT_DIR\n",
            "    directory\n",
            "    to save the\n",
            "    outputs\n",
            "    (default:\n",
            "    .)\n",
            "  --output_format {txt,vtt,srt,tsv,json,all}, -f {txt,vtt,srt,tsv,json,all}\n",
            "    format of\n",
            "    the output\n",
            "    file; if\n",
            "    not\n",
            "    specified,\n",
            "    all\n",
            "    available\n",
            "    formats\n",
            "    will be\n",
            "    produced\n",
            "    (default:\n",
            "    all)\n",
            "  --verbose VERBOSE\n",
            "    whether to\n",
            "    print out\n",
            "    the\n",
            "    progress\n",
            "    and debug\n",
            "    messages\n",
            "    (default:\n",
            "    True)\n",
            "  --task {transcribe,translate}\n",
            "    whether to\n",
            "    perform\n",
            "    X->X speech\n",
            "    recognition\n",
            "    ('transcrib\n",
            "    e') or\n",
            "    X->English\n",
            "    translation\n",
            "    ('translate\n",
            "    ')\n",
            "    (default:\n",
            "    transcribe)\n",
            "  --language {af,am,ar,as,az,ba,be,bg,bn,bo,br,bs,ca,cs,cy,da,de,el,en,es,et,eu,fa,fi,fo,fr,gl,gu,ha,haw,he,hi,hr,ht,hu,hy,id,is,it,ja,jw,ka,kk,km,kn,ko,la,lb,ln,lo,lt,lv,mg,mi,mk,ml,mn,mr,ms,mt,my,ne,nl,nn,no,oc,pa,pl,ps,pt,ro,ru,sa,sd,si,sk,sl,sn,so,sq,sr,su,sv,sw,ta,te,tg,th,tk,tl,tr,tt,uk,ur,uz,vi,yi,yo,zh,Afrikaans,Albanian,Amharic,Arabic,Armenian,Assamese,Azerbaijani,Bashkir,Basque,Belarusian,Bengali,Bosnian,Breton,Bulgarian,Burmese,Castilian,Catalan,Chinese,Croatian,Czech,Danish,Dutch,English,Estonian,Faroese,Finnish,Flemish,French,Galician,Georgian,German,Greek,Gujarati,Haitian,Haitian Creole,Hausa,Hawaiian,Hebrew,Hindi,Hungarian,Icelandic,Indonesian,Italian,Japanese,Javanese,Kannada,Kazakh,Khmer,Korean,Lao,Latin,Latvian,Letzeburgesch,Lingala,Lithuanian,Luxembourgish,Macedonian,Malagasy,Malay,Malayalam,Maltese,Maori,Marathi,Moldavian,Moldovan,Mongolian,Myanmar,Nepali,Norwegian,Nynorsk,Occitan,Panjabi,Pashto,Persian,Polish,Portuguese,Punjabi,Pushto,Romanian,Russian,Sanskrit,Serbian,Shona,Sindhi,Sinhala,Sinhalese,Slovak,Slovenian,Somali,Spanish,Sundanese,Swahili,Swedish,Tagalog,Tajik,Tamil,Tatar,Telugu,Thai,Tibetan,Turkish,Turkmen,Ukrainian,Urdu,Uzbek,Valencian,Vietnamese,Welsh,Yiddish,Yoruba}\n",
            "    language\n",
            "    spoken in\n",
            "    the audio,\n",
            "    specify\n",
            "    None to\n",
            "    perform\n",
            "    language\n",
            "    detection\n",
            "    (default:\n",
            "    None)\n",
            "  --temperature TEMPERATURE\n",
            "    temperature\n",
            "    to use for\n",
            "    sampling\n",
            "    (default:\n",
            "    0)\n",
            "  --best_of BEST_OF\n",
            "    number of\n",
            "    candidates\n",
            "    when\n",
            "    sampling\n",
            "    with non-\n",
            "    zero\n",
            "    temperature\n",
            "    (default:\n",
            "    5)\n",
            "  --beam_size BEAM_SIZE\n",
            "    number of\n",
            "    beams in\n",
            "    beam\n",
            "    search,\n",
            "    only\n",
            "    applicable\n",
            "    when\n",
            "    temperature\n",
            "    is zero\n",
            "    (default:\n",
            "    5)\n",
            "  --patience PATIENCE\n",
            "    optional\n",
            "    patience\n",
            "    value to\n",
            "    use in beam\n",
            "    decoding,\n",
            "    as in https\n",
            "    ://arxiv.or\n",
            "    g/abs/2204.\n",
            "    05424, the\n",
            "    default\n",
            "    (1.0) is\n",
            "    equivalent\n",
            "    to conventi\n",
            "    onal beam\n",
            "    search\n",
            "    (default:\n",
            "    None)\n",
            "  --length_penalty LENGTH_PENALTY\n",
            "    optional\n",
            "    token\n",
            "    length\n",
            "    penalty\n",
            "    coefficient\n",
            "    (alpha) as\n",
            "    in https://\n",
            "    arxiv.org/a\n",
            "    bs/1609.081\n",
            "    44, uses\n",
            "    simple\n",
            "    length norm\n",
            "    alization\n",
            "    by default\n",
            "    (default:\n",
            "    None)\n",
            "  --suppress_tokens SUPPRESS_TOKENS\n",
            "    comma-\n",
            "    separated\n",
            "    list of\n",
            "    token ids\n",
            "    to suppress\n",
            "    during\n",
            "    sampling;\n",
            "    '-1' will\n",
            "    suppress\n",
            "    most\n",
            "    special\n",
            "    characters\n",
            "    except\n",
            "    common punc\n",
            "    tuations\n",
            "    (default:\n",
            "    -1)\n",
            "  --initial_prompt INITIAL_PROMPT\n",
            "    optional\n",
            "    text to\n",
            "    provide as\n",
            "    a prompt\n",
            "    for the\n",
            "    first\n",
            "    window.\n",
            "    (default:\n",
            "    None)\n",
            "  --condition_on_previous_text CONDITION_ON_PREVIOUS_TEXT\n",
            "    if True,\n",
            "    provide the\n",
            "    previous\n",
            "    output of\n",
            "    the model\n",
            "    as a prompt\n",
            "    for the\n",
            "    next\n",
            "    window;\n",
            "    disabling\n",
            "    may make\n",
            "    the text in\n",
            "    consistent\n",
            "    across\n",
            "    windows,\n",
            "    but the\n",
            "    model\n",
            "    becomes\n",
            "    less prone\n",
            "    to getting\n",
            "    stuck in a\n",
            "    failure\n",
            "    loop\n",
            "    (default:\n",
            "    True)\n",
            "  --fp16 FP16\n",
            "    whether to\n",
            "    perform\n",
            "    inference\n",
            "    in fp16;\n",
            "    True by\n",
            "    default\n",
            "    (default:\n",
            "    True)\n",
            "  --temperature_increment_on_fallback TEMPERATURE_INCREMENT_ON_FALLBACK\n",
            "    temperature\n",
            "    to increase\n",
            "    when\n",
            "    falling\n",
            "    back when\n",
            "    the\n",
            "    decoding\n",
            "    fails to\n",
            "    meet either\n",
            "    of the\n",
            "    thresholds\n",
            "    below\n",
            "    (default:\n",
            "    0.2)\n",
            "  --compression_ratio_threshold COMPRESSION_RATIO_THRESHOLD\n",
            "    if the gzip\n",
            "    compression\n",
            "    ratio is\n",
            "    higher than\n",
            "    this value,\n",
            "    treat the\n",
            "    decoding as\n",
            "    failed\n",
            "    (default:\n",
            "    2.4)\n",
            "  --logprob_threshold LOGPROB_THRESHOLD\n",
            "    if the\n",
            "    average log\n",
            "    probability\n",
            "    is lower\n",
            "    than this\n",
            "    value,\n",
            "    treat the\n",
            "    decoding as\n",
            "    failed\n",
            "    (default:\n",
            "    -1.0)\n",
            "  --no_speech_threshold NO_SPEECH_THRESHOLD\n",
            "    if the\n",
            "    probability\n",
            "    of the <|no\n",
            "    speech|>\n",
            "    token is\n",
            "    higher than\n",
            "    this value\n",
            "    AND the\n",
            "    decoding\n",
            "    has failed\n",
            "    due to `log\n",
            "    prob_thresh\n",
            "    old`,\n",
            "    consider\n",
            "    the segment\n",
            "    as silence\n",
            "    (default:\n",
            "    0.6)\n",
            "  --word_timestamps WORD_TIMESTAMPS\n",
            "    (experiment\n",
            "    al) extract\n",
            "    word-level\n",
            "    timestamps\n",
            "    and refine\n",
            "    the results\n",
            "    based on\n",
            "    them\n",
            "    (default:\n",
            "    False)\n",
            "  --prepend_punctuations PREPEND_PUNCTUATIONS\n",
            "    if word_tim\n",
            "    estamps is\n",
            "    True, merge\n",
            "    these\n",
            "    punctuation\n",
            "    symbols\n",
            "    with the\n",
            "    next word\n",
            "    (default:\n",
            "    \"'“¿([{-)\n",
            "  --append_punctuations APPEND_PUNCTUATIONS\n",
            "    if word_tim\n",
            "    estamps is\n",
            "    True, merge\n",
            "    these\n",
            "    punctuation\n",
            "    symbols\n",
            "    with the\n",
            "    previous\n",
            "    word\n",
            "    (default: \"\n",
            "    '.。,，!！?？:：\n",
            "    ”)]}、)\n",
            "  --highlight_words HIGHLIGHT_WORDS\n",
            "    (requires -\n",
            "    -word_times\n",
            "    tamps True)\n",
            "    underline\n",
            "    each word\n",
            "    as it is\n",
            "    spoken in\n",
            "    srt and vtt\n",
            "    (default:\n",
            "    False)\n",
            "  --max_line_width MAX_LINE_WIDTH\n",
            "    (requires -\n",
            "    -word_times\n",
            "    tamps True)\n",
            "    the maximum\n",
            "    number of\n",
            "    characters\n",
            "    in a line\n",
            "    before\n",
            "    breaking\n",
            "    the line\n",
            "    (default:\n",
            "    None)\n",
            "  --max_line_count MAX_LINE_COUNT\n",
            "    (requires -\n",
            "    -word_times\n",
            "    tamps True)\n",
            "    the maximum\n",
            "    number of\n",
            "    lines in a\n",
            "    segment\n",
            "    (default:\n",
            "    None)\n",
            "  --threads THREADS\n",
            "    number of\n",
            "    threads\n",
            "    used by\n",
            "    torch for\n",
            "    CPU\n",
            "    inference;\n",
            "    supercedes \n",
            "    MKL_NUM_THR\n",
            "    EADS/OMP_NU\n",
            "    M_THREADS\n",
            "    (default:\n",
            "    0)\n"
          ]
        }
      ]
    }
  ]
}