Combining Global and Local Classifiers for Lipreading

Authors:
Shengping Zhang;Hongxun Yao;Yuqi Wan;Dan Wang
Affiliations:
School of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China;School of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China;School of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China;School of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China
Venue:
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Year:
2007

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Abstract

Lipreading has become a hot research topic in recent years since the visual information extracted from the lip movement has been shown to improve the performance of automatic speech recognition (ASR) system especially under noisy environments [1]-[3], [5]. There are two important issues related to lipreading: 1) how to extract the most efficient features from lip image sequences, 2) how to build lipreading models. This paper mainly focuses on how to choose more efficient features for lipreading.