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View guide →Entirely speech-to-speech translation pipeline with voice cloning (RVC) and automatic
speech-to-speech-with-lipsync is an open-source video project by M-SRIKAR-VARDHAN (M-SRIKAR-VARDHAN/speech-to-speech-with-lipsync on GitHub). It has 36 GitHub stars and 7 forks, is released under the Custom license, and was last updated on GitHub on 24 March 2026.
Clone M-SRIKAR-VARDHAN/speech-to-speech-with-lipsync and move into the project folder.
Install the Python requirements with pip — a virtual environment keeps things clean.
Gather the video or audio files you want to work with.
Start the job and check the output folder.
Built around artificial intelligence from the ground up.
Deep learning models at the core.
Media processing handled by FFmpeg under the hood.
Focused on lip synchronization as a core part of the project.
Neural machine translation.
Python codebase — easy to read, fork, and extend.
Download the source and move into the project folder.
git clone https://github.com/M-SRIKAR-VARDHAN/speech-to-speech-with-lipsync.git
cd speech-to-speech-with-lipsyncSet up what the project needs to run.
pip install -r requirements.txtStart the app — the README has the exact command and flags.
python main.py # entrypoint varies — check the READMEIt ships under a custom license — read the terms before commercial use.
Clone the repo and pip-install the requirements — the README covers the exact steps.
The GitHub repo's issues and discussions are the main support channel.
Last pushed 2026-03-24 with 7 forks. Skim recent commits to gauge momentum before relying on it.
Yes — it is open source, so issues and pull requests are welcome.
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