Subtitle

Open-source subtitle generation for seamless content translation.

Key Features:

• Open-source: Freely available for use, modification, and distribution.
• Self-hosted: Run the tool on your own servers for enhanced control and privacy.
• AI-powered: Leverage advanced machine learning for accurate and natural-sounding subtitles.
• Multilingual support: Generate subtitles for videos in a wide range of languages.
• Easy integration: Seamlessly integrates into your existing workflow.

I made this project for fun, but I think it could also be useful for other people.

Installation

FFmpeg

First, you need to install FFmpeg. Here's how you can do it:

# On Linux
sudo apt install ffmpeg

Run

You can run the script from the command line using the following command:

python subtitle.py <filepath | video_url> [--model <modelname>]

Replace <filepath | video_url> with the path to your video file. The --model argument is optional. If not provided, it will use 'base' as the default model.

For example:

python subtitle.py /path/to/your/video.mp4 --model base

This will run the script on the video at /path/to/your/video.mp4 using the base model. Please replace /path/to/your/video.mp4 with the actual path to your video file.

Models

Here are the models you can use: Note: Use the .en model only when the video is in English.

• tiny.en
• tiny
• tiny-q5_1
• tiny.en-q5_1
• base.en
• base
• base-q5_1
• base.en-q5_1
• small.en
• small.en-tdrz
• small
• small-q5_1
• small.en-q5_1
• medium
• medium.en
• medium-q5_0
• medium.en-q5_0
• large-v1
• large-v2
• large
• large-q5_0

Advance

You can modify the behaviour by using these parameters whisper binary as follows:

./whisper [options] file0.wav file1.wav ...

Options

Here are the options you can use with the whisper binary:

Option	Default	Description
-h, --help		Show help message and exit
-t N, --threads N	4	Number of threads to use during computation
-p N, --processors N	1	Number of processors to use during computation
-ot N, --offset-t N	0	Time offset in milliseconds
-on N, --offset-n N	0	Segment index offset
-d N, --duration N	0	Duration of audio to process in milliseconds
-mc N, --max-context N	-1	Maximum number of text context tokens to store
-ml N, --max-len N	0	Maximum segment length in characters
-sow, --split-on-word	false	Split on word rather than on token
-bo N, --best-of N	2	Number of best candidates to keep
-bs N, --beam-size N	-1	Beam size for beam search
-wt N, --word-thold N	0.01	Word timestamp probability threshold
-et N, --entropy-thold N	2.40	Entropy threshold for decoder fail
-lpt N, --logprob-thold N	-1.00	Log probability threshold for decoder fail
-debug, --debug-mode	false	Enable debug mode (eg. dump log_mel)
-tr, --translate	false	Translate from source language to English
-di, --diarize	false	Stereo audio diarization
-tdrz, --tinydiarize	false	Enable tinydiarize (requires a tdrz model)
-nf, --no-fallback	false	Do not use temperature fallback while decoding
-otxt, --output-txt	true	Output result in a text file
-ovtt, --output-vtt	false	Output result in a vtt file
-osrt, --output-srt	false	Output result in a srt file
-olrc, --output-lrc	false	Output result in a lrc file
-owts, --output-words	false	Output script for generating karaoke video
-fp, --font-path	/System/Library/Fonts/Supplemental/Courier New Bold.ttf	Path to a monospace font for karaoke video
-ocsv, --output-csv	false	Output result in a CSV file
-oj, --output-json	false	Output result in a JSON file
-ojf, --output-json-full	false	Include more information in the JSON file
-of FNAME, --output-file FNAME		Output file path (without file extension)
-ps, --print-special	false	Print special tokens
-pc, --print-colors	false	Print colors
-pp, --print-progress	false	Print progress
-nt, --no-timestamps	false	Do not print timestamps
-l LANG, --language LANG	en	Spoken language ('auto' for auto-detect)
-dl, --detect-language	false	Exit after automatically detecting language
--prompt PROMPT		Initial prompt
-m FNAME, --model FNAME	models/ggml-base.en.bin	Model path
-f FNAME, --file FNAME		Input WAV file path
-oved D, --ov-e-device DNAME	CPU	The OpenVINO device used for encode inference
-ls, --log-score	false	Log best decoder scores of tokens
-ng, --no-gpu	false	Disable GPU

Example for running Binary

Here's an example of how to use the whisper binary:

./whisper -m models/ggml-tiny.en.bin -f Rev.mp3 out.wav -nt --output-vtt

License

MIT

Reference & Credits

• https://github.com/openai/whisper
• https://openai.com/blog/whisper/
• https://github.com/ggerganov/whisper.cpp
• https://github.com/innovatorved/whisper.api

Authors

• Ved Gupta

🚀 About Me

Just try to being a Developer!

Support

For support, email vedgupta@protonmail.com