A PyTorch implementation of the Deep Audio-Visual Speech Recognition paper.
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Updated
Feb 15, 2024 - Python
A PyTorch implementation of the Deep Audio-Visual Speech Recognition paper.
A pipeline to read lips and generate speech for the read content, i.e Lip to Speech Synthesis.
End-to-end pipeline for lip reading at the word level using a tensorflow CNN implementation.
My experiments in lip reading using deep learning with the LRW dataset
My experiments with lip reading using GRIDcorpus dataset
Automated Lip Reading using Deep Reinforcement Learning
Our project's source code and documentation as part of the requirements for Graduation Project-2 (CCEN481) in Computer Engineering Program at Cairo University Faculty of Engineering
Speaker-Independent Speech Recognition using Visual Features
Visual speech recognition with face inputs: code and models for F&G 2020 paper "Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech Recognition"
An open-source library for recognition of speech commands in the user dictionary using audiovisual data of the speaker
The official implementation of OpenSR (ACL2023 Oral)
In this project, visual speech recognition has been attempted using 2 major machine learning techniques namely CNN and HMM. We also compare the efficiencies of Character and Word based CNN models. Miracl-VC1 Dataset was used to train all the models
EMOLIPS: TWO-LEVEL APPROACH FOR LIP-READING EMOTIONAL SPEECH
In this repository, I try to use k2, icefall and Lhotse for lip reading. I will modify it for the lip reading task. Many different lip-reading datasets should be added. -_-
A novel lipreading system that improves on the task of speaker-independent word recognition by decoupling motion and content dynamics.
An multi modal automated proctor for online exams
Code repo for NTUA DSML MSc thesis
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