chnkvn / audio-video-transcriber

A tool to transcribe media files.

Audio-Video-Transcriber

Whisper-cpu

This repository offers a way to transcribe media files on cpu using distil-whisper and faster-whisper. Files can be found online (e.g. a youtube video, paste its url on the app, or uploaded from local).

Installation

• Ensure to install ffmpeg binary
• clone this repo
• run pip install -r requirements.txt
  • run pip install gradio ; it is not included in requirements.txt due to a dependency conflict with yt-dlp and gradio (websockets version)
• first clone bofenghuang/whisper-large-v3-french-distil-dec16 at root level of this repository, using python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='bofenghuang/whisper-large-v3-french-distil-dec16', local_dir='./models/whisper-large-v3-french-distil-dec16', allow_patterns='ctranslate2/*')"
• go to models/ ; clone this two repositories: Systran/faster-distil-whisper-large-v2, Systran/faster-whisper-large-v2
• you can run the unit tests by moving to tests folder and using python -m unittest tests -v
• run the app using python whisper_cpu/app.py

Docker

You can perform an install by building a docker image :

• clone this repo
• build the image
• run the container. Make sure to redirect the port 7860 of the container to a port on your local machine.

No need to download the models, they will be downloaded during the image building process.

Models

• faster-distil-whisper-large-v2 : a distilled model of whisper-v3 for English
• bofenghuang/whisper-large-v3-french-distil-dec16 : a distilled model of whisper-v3 for French
• faster-whisper-large-v2 : a multilingual model. Slower than the above models.

v3 versions of Whisper are more prone to hallucination than v2, that’s why I choose to use the latter when they are available.

Notebook

This repository also contains a notebook, and must be used with a GPU for performance. A colab GPU is enough. It uses whisper3 and gradio. To run it, you can:

• Import the notebook on a google colab instance
• Activate the GPU
• Run all the cells
• Scroll to the last cell and wait until a visual interface appears
• Use the app

Features:

• Youtube video transcripter: Transcribe the content of a

youtube video to a text file, one sentence per line separated by an empty new line or a srt file with timestamps.

• Local audio/video file transcripter: Same as the youtube video transcripter, but for your local

audio/video files.

• Chunk reorder: After reviewing a srt file, assign

an unique number to each chun to get them ordered.