Wav2Lip
Open-source lip sync that animates any face to match audio.
About
Wav2Lip is an open-source lip-sync model developed at IIIT Hyderabad that generates realistic mouth movements on any face to match a given audio track. It works on still photos as well as existing video, which makes it a standard tool for dubbing and talking-head generation.
It is lighter and faster than full talking-head models, running several times faster than alternatives while keeping strong sync accuracy. The tradeoff is that head pose stays mostly static, with the model overlaying a lip-sync patch on the face.
What it can do
- Accurate lip sync from any audio input
- Works on photos and existing video
- Lightweight and fast inference
- Multilingual dubbing support
Setup
Clone the Rudrabha/Wav2Lip repository, install the requirements, download the pretrained weights into the checkpoints folder, then run the inference script with a face image and an audio file.
Prerequisites
Python 3.10, PyTorch, ffmpeg, and the pretrained checkpoint files.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 131; Trending score 76/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.