lip-reading-deeplearning

Why we included this project

This is a TensorFlow implementation of coupled 3D convolutional networks for audio-visual speech recognition, matching lip-motion video against the corresponding speech stream. It accompanies a published IEEE paper and shows how to model spatial and temporal information together so the two modalities can back each other up when the audio is noisy or missing. A lip-tracking script extracts and visualizes the mouth region from an input video, which helps when you're building the visual input pipeline. The authors expect you to handle your own feature extraction and dataset, so treat it as a study resource and a starting point for reproducing or extending the approach rather than something you can drop into a project. If you're working on multimodal recognition or speaker verification, it's worth reading for the architecture ideas and preprocessing patterns.