DocumentCode :
1884175
Title :
Sensory integration in audiovisual automatic speech recognition
Author :
Silsbee, Peter L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA
Volume :
1
fYear :
1994
fDate :
31 Oct-2 Nov 1994
Firstpage :
561
Abstract :
Methods of integrating audio and visual information in an audiovisual HMM-based ASR system are investigated. Experiments involve discrimination of a set of 22 consonants, with various integration strategies. The role of the visual subsystem is varied; for example, in one run, the subsystem attempts to classify all 22 consonants, while in other runs it attempts only broader classifications. In a second experiment, a new HMM formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A single variable parameter allows the relative contribution of audio and visual information to be controlled. This form of integration can be very easily incorporated into existing audio-based continuous speech recognizers
Keywords :
audio-visual systems; hidden Markov models; speech recognition; audio information; audio-based continuous speech recognizers; audiovisual HMM-based ASR system; audiovisual automatic speech recognition; classifications; consonants; experiments; integration strategies; sensory integration; visual information; visual subsystem; Automatic control; Automatic speech recognition; Cameras; Degradation; Hidden Markov models; Humans; Loudspeakers; Microphones; Optical arrays; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
0-8186-6405-3
Type :
conf
DOI :
10.1109/ACSSC.1994.471515
Filename :
471515
Link To Document :
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