A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is
The aim of the present study is to investigate some key challenges of the audio-visual speech recognition technology, such as asynchrony modeling of multimodal speech, estimation of auditory and visual speech significance, as well as stream weight optimization. Our research shows that the use of viseme-dependent significance weights improves the performance of state asynchronous CHMM-based speech recognizer. In addition, for a state synchronous MSHMMbased recognizer, fewer errors can bedoi:10.21437/interspeech.2010-710 fatcat:tgeqx4u6yzebnixfhofmozlosu