A PyTorch implementation of the Deep Audio-Visual Speech Recognition paper.

Automated Lip reading from real-time videos in tensorflow in python

A pipeline to read lips and generate speech for the read content, i.e Lip to Speech Synthesis.

My experiments in lip reading using deep learning with the LRW dataset

End-to-end pipeline for lip reading at the word level using a tensorflow CNN implementation.

Automated Lip Reading using Deep Reinforcement Learning

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"

Deep Visual Speech Recognition in arabic words

The official implementation of OpenSR (ACL2023 Oral)

My experiments with lip reading using GRIDcorpus dataset

An open-source library for recognition of speech commands in the user dictionary using audiovisual data of the speaker

EMOLIPS: TWO-LEVEL APPROACH FOR LIP-READING EMOTIONAL SPEECH

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

My experiments with Zero Shot Learning

Speaker-Independent Speech Recognition using Visual Features

SYDE 522: Machine Intelligence course project on automated lip reading.

Code repo for NTUA DSML MSc thesis

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. -_-

An multi modal automated proctor for online exams

Deep Visual Speech Recognition in arabic words

Repository for the paper "Lip Reading in unconstrained driving scenario with Greek words"

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

🔍 Read lips in videos with an end-to-end deep learning model, enhancing accessibility and transcribing speech from mouth movements effectively.

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This is an AI enhanced lip reading application based on real-world videos from GRID corpus

Deep Learning Approach for Lip reading in Real-Time

Automatic Lip reading Model using 3D CNN and GRU

This model seeks to decipher sequences of lip movements captured in video frames and translate them into meaningful spoken language or phonetic representations.

This repository implements a word-level lip reading approach using a CNN-LSTM architecture. The model and preprocessing pipeline are designed for the German Lip Reading Dataset (GLips)

Deep learning lip-reading model using Conv3D + BiLSTM + CTC architecture. Transcribes speech from mouth region video clips for accessibility applications.