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Automatically generate, translate and overlay subtitles for any video.

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Automatic subtitles in your videos

This is a fork of auto_subtitle using faster-whisper implementation.

This repository uses ffmpeg and OpenAI's Whisper to automatically generate and overlay subtitles on any video.

It also uses Opus-MT to translate subtitles to another language.

While both transcription and translation are offline processes they require downloading pre-trained models that require some time to load on the first run.

Installation

To get started, you'll need Python 3.9 or newer. Install the binary by running the following command:

pip install --no-deps EasyNMT==2.0.2

pip install git+https://github.com/Sirozha1337/faster-auto-subtitle.git

You'll also need to install ffmpeg, which is available from most package managers:

# on Ubuntu or Debian
sudo apt update && sudo apt install ffmpeg

# on MacOS using Homebrew (https://brew.sh/)
brew install ffmpeg

# on Windows using Chocolatey (https://chocolatey.org/)
choco install ffmpeg

Usage

The following command will generate a subtitled/video.mp4 file contained the input video with overlayed subtitles.

faster_auto_subtitle /path/to/video.mp4 -o subtitled/

The default setting (which selects the small model) works well for transcribing English. You can optionally use a bigger model for better results (especially with other languages). The available models are tiny, tiny.en, base, base.en, small, small.en, medium, medium.en, large, large-v1, large-v2, large-v3.

faster_auto_subtitle /path/to/video.mp4 --model medium

Adding --task translate will translate the subtitles into English:

faster_auto_subtitle /path/to/video.mp4 --task translate

Adding --target_language {2-letter-language-code} will translate the subtitles into specified language using Opus-MT:

faster_auto_subtitle /path/to/video.mp4 --target_language fr

This will require downloading the appropriate model. If direct translation is not available it will attempt translation from source to english and from english to source.

Run the following to view all available options:

faster_auto_subtitle --help

Tips

The tool also exposes a couple of model parameters, that you can tweak to increase accuracy.

Higher beam_size usually leads to greater accuracy, but slows down the process.

Setting higher no_speech_threshold could be useful for videos with a lot of background noise to stop Whisper from " hallucinating" subtitles for it.

In my experience settings option condition_on_previous_text to False dramatically increases accuracy for videos like TV Shows with an intro song at the start.

You can use sample_interval parameter to generate subtitles for a portion of the video to play around with those parameters:

faster_auto_subtitle /path/to/video.mp4 --model medium --sample_interval 00:05:30-00:07:00 --condition_on_previous_text False --beam_size 6 --no_speech_threshold 0.7

License

This script is open-source and licensed under the MIT License. For more details, check the LICENSE file.