A hidden Markov model based visual speech synthesizer

被引:0
|
作者
Williams, JJ [1 ]
Katsaggelos, AK [1 ]
Randolph, MA [1 ]
机构
[1] Northwestern Univ, Dept Elect & Comp Engn, Evanston, IL 60202 USA
关键词
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
This paper describes a hidden Markov model (HMM) based visual synthesizer designed to assist persons with impaired-hearing. This synthesizer builds on results in the area of audio-visual speech recognition. We describe how a correlation HMM can be used to integrate independent acoustic and visual HMMs for speech-to-visual synthesis. Our results show that an HMM correlating model can significantly improve synchronization errors versus techniques which compensate for rate differences through scaling.
引用
收藏
页码:2393 / 2396
页数:4
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