DocumentCode :
284654
Title :
Use of acoustic sentence level and lexical stress in HSMM speech recognition
Author :
Hieronymus, J.L. ; McKelvie, D. ; McInnes, F.R.
Author_Institution :
Center for Speech Technol. Res., Edinburgh Univ., UK
Volume :
1
fYear :
1992
fDate :
23-26 Mar 1992
Firstpage :
225
Abstract :
The authors describe the results of an experiment to study the effectiveness of using acoustic stress to improve automatic speech recognition. The CSTR speech recognition system uses hidden semi-Markov models (HSMM) with a separate lexical search component. A hybrid prosodic component has been included which determines the sentence level stress and marks the vowel of stressed syllables as stressed in the phoneme lattice. Lexical stress is marked on all content words in the lexicon. Adding stress information to the system in this way resulted in a 65% reduction in word error rate and a 45% reduction in sentence error rate, relative to a baseline system without prosody
Keywords :
error statistics; hidden Markov models; speech recognition; HSMM speech recognition; acoustic sentence level; acoustic stress; automatic speech recognition; hybrid prosodic component; lexical stress; sentence error rate; sentence level stress; word error rate; Automatic speech recognition; Bridges; Continuous-stirred tank reactor; Costs; Dynamic programming; Error analysis; Lattices; Matrices; Speech recognition; Stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1520-6149
Print_ISBN :
0-7803-0532-9
Type :
conf
DOI :
10.1109/ICASSP.1992.225931
Filename :
225931
Link To Document :
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