基于Vision Transformer的中文唇语识别

doi:10.16451/j.cnki.issn1003-6059.202212006

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Abstract Lipreading is a multimodal task to convert lipreading videos into text, and it is intended to understand the meaning expressed by a speaker in the absence of sound. In the existing lipreading methods, convolutional neural networks are adopted to extract visual features of the lips and capture short-distance pixel relationships, resulting in difficulties in distinguishing lip shapes of similarly pronounced characters. To capture the long-distance relationship between pixels in the lip region of the video images, an end-to-end Chinese sentence-level lipreading model based on vision transformer(ViT) is proposed. The ability of the model to extract visual spatio-temporal features from lip videos is improved by fusing ViT and Gate Recurrent Unit(GRU). Firstly, the global spatial features of lip images are extracted using the self-attention module of ViT. Then, GRU is employed to model the temporal sequence of frames. Finally, the cascading sequence-to-sequence model based on the attention mechanism is utilized to predict Chinese pinyin and Chinese character utterances. Experimental results on Chinese lipreading dataset CMLR show that the proposed model produces a lower Chinese character error rate.

Key words： Lipreading Vision Transformer(ViT) Deep Neural Network Encoder-Decoder Attention Mechanism Feature Extraction

Received: 08 July 2022

ZTFLH:

TP391.41

Fund:National Natural Science Foundation of China(No.62272143), University Synergy Innovation Program of Anhui Province(No.GXXT-2022-054), Anhui Provincial Major Science and Technology Project(No.202203a05020025), The Se-venth Special Support Plan for Innovation and Entrepreneurship in Anhui Province

Corresponding Authors: XUE Feng, Ph.D., professor. His research interests include artificial intelligence, multimedia analysis and recommendation system.

About author:: HONG Zikun, master student. His research interests include computer vision.LI Shujie, Ph.D., lecturer. Her research interests include computer vision and human pose estimation.LI Yu, Ph.D. candidate. Her research interests include computer vision.XIE Yincen, master student. His research interests include computer vision.

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	XUE Feng
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Cite this article:

XUE Feng,HONG Zikun,LI Shujie等. Chinese Lipreading Network Based on Vision Transformer[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(12): 1111-1121.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202212006 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I12/1111

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