Experiments on stress-dependent phone modelling for continuous speech recognition

Stress is an important feature for speech recognition. The acoustic realization of a stressed phone trends to be rather different from its unstressed counterpart, and stress may be a distinctive feature for lexical classification, as in the case for English. In most cases stress is important for und...

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Bibliographic Details
Main Authors: Adda-Decker, M., Adda, G.
Format: Conference Proceeding
Language:English
Subjects:
Context modeling
Frequency
Hidden Markov models
Loudspeakers
Natural languages
Proposals
Spatial databases
Speech recognition
Stress
Training data
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Summary:Stress is an important feature for speech recognition. The acoustic realization of a stressed phone trends to be rather different from its unstressed counterpart, and stress may be a distinctive feature for lexical classification, as in the case for English. In most cases stress is important for understanding the meaning of an utterance, and is thus related to syntax and semantics. The authors focus on the acoustic modeling of stressed phones, and, particularly, on stressed vowels. The recognition system is based on discrete HMM phone models, and has been developed within the European ESPRIT-POLYGLOT 2041 project. The influence of the stress feature on acoustic modeling is being assessed on two different continuous speech databases in two different languages (French and American-English), as the effect of stress on the acoustic evidence may be language-dependent. First results concerning phonetic and lexical evaluations are given.< >
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1992.225846