Automated Lip reading from real-time videos in tensorflow in python
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Updated
Mar 20, 2018 - Jupyter Notebook
Automated Lip reading from real-time videos in tensorflow in 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
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"
SYDE 522: Machine Intelligence course project on automated lip reading.
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
An open-source library for recognition of speech commands in the user dictionary using audiovisual data of the speaker
Repository for the paper "Lip Reading in unconstrained driving scenario with Greek words"
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
Deep Visual Speech Recognition in arabic words
Deep Learning Approach for Lip reading in Real-Time
Inspired by the LipNet Paper at https://arxiv.org/abs/1611.01599 and the Visual Speech Recognition for Multiple Languages in the Wild paper at https://arxiv.org/pdf/2202.13084v2.pdf
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