A Lip Reading Method Based on 3D Convolutional Vision Transformer

Author:

Wang Huijuan1ORCID,Pu Gangqiang1,Chen Tingyu1

Affiliation:

1. Department of Computer, North China Institute of Aerospace Engineering, Langfang, China

Funder

Scientific Research Key Project of Hebei Provincial Department of Education

Natural Science Foundation of Hebei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference44 articles.

1. Empirical evaluation of gated recurrent neural networks on sequence modeling;chung;arXiv 1412 3555,2014

2. Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

3. Attention is all you need;aswani;Proc NIPS,2017

4. LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild

5. Lip reading in the wild;js;Proc Asian Conf Comput Vis,2016

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1. AI Lip Reader Detecting Speech Visual Data with Deep Learning;2023 4th International Conference on Intelligent Technologies (CONIT);2024-06-21

2. Mini-3DCvT: a lightweight lip-reading method based on 3D convolution visual transformer;The Visual Computer;2024-06-11

3. Deep hybrid architectures and DenseNet35 in speaker-dependent visual speech recognition;Signal, Image and Video Processing;2024-05-02

4. An Extensive Investigation of Deep Learning Techniques for Audio-Visual Speech Recognition;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

5. LipSyncNet: A Novel Deep Learning Approach for Visual Speech Recognition in Audio-Challenged Situations;IEEE Access;2024

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