The state-of-art PyTorch implementation of the method described in the paper "LipNet: End-to-End Sentence-level Lipreading" (https://arxiv.org/abs/1611.01599)
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Updated
Sep 21, 2022 - Python
The state-of-art PyTorch implementation of the method described in the paper "LipNet: End-to-End Sentence-level Lipreading" (https://arxiv.org/abs/1611.01599)
Visual Speech Recognition for Multiple Languages
The PyTorch Code and Model In "Learn an Effective Lip Reading Model without Pains", (https://arxiv.org/abs/2011.07557), which reaches the state-of-art performance in LRW-1000 dataset.
Auto-AVSR: Lip-Reading Sentences Project
Audio-Visual Speech Recognition using Sequence to Sequence Models
DenseNet3D Model In "LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild", https://arxiv.org/abs/1810.06990
"LipNet: End-to-End Sentence-level Lipreading" in PyTorch
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.
A Keras implementation of LipNet
PyTorch models for lipreading words and sentences
This project aims to develop and test different lip reading algorithms on words and on sentences, using the GRID Corpus Dataset.
Speaker-Independent Speech Recognition using Visual Features
The concurrent lipreader for the smart masses (DC27 AI Village)
Implementation of "Combining Residual Networks with LSTMs for Lipreading" in Keras and Tensorflow2.0
Implementation of a method to lipreading using landmark from 3D talking head
Chainer code for using Residual Networks with LSTMs for Lipreading
Replication of the state-of-the-art LIPNET model for end-to-end sentence-level lipreading.
Курсовой проект по теме "Анализ эффективности архитектур визуального распознавания речи"
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