Integration of acoustic and visual speech signals using neural networks (1989)
| Venue: | IEEE Communications Magazine |
| Citations: | 27 - 0 self |
BibTeX
@ARTICLE{Yuhas89integrationof,
author = {Ben P. Yuhas and Moise H. Goldstein and Terrence J. Sejnowski},
title = {Integration of acoustic and visual speech signals using neural networks},
journal = {IEEE Communications Magazine},
year = {1989}
}
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Abstract
rely almost exclusively on the acoustic speech signal and, consequently, these systems often perform poorly in noisy environments [I]. Attempts to clean up the acoustic input have had limited success [2]. Another approach is to use other sources of speech information, such as visual speech signals. The perception of acoustic speech by humans can be affected by the visible speech signals [3-51. Specifically, when the acoustic signal is degraded by noise, the visual signal can provide supplemental speech information that improves speech perception [6-81. When no acoustic signal is available, as for the profoundly deaf, the visual signal alone can provide speech information through lip reading [9- 1 I]. Here we answer two questions: Can the speech information conveyed by visual speech signals be extracted automatically? How can this information be combined with information from the acoustic signal to improve automat
