DocumentCode :
290118
Title :
An efficient combination of acoustic and supra-segmental informations in a speech recognition system
Author :
Suaudeau, Nelly ; André-Obrecht, Régine
Author_Institution :
IRISA, Rennes, France
Volume :
i
fYear :
1994
fDate :
19-22 Apr 1994
Abstract :
A major deficiency of a standard HMM is that both the spectral and the prosodic features are uniformly processed. To more efficiently combine the prosodic cues together with the acoustic ones, a two level HMM which separates the spectral and suprasegmental representations is defined. Namely, the incorporation of global sound durations is explored. More, to take into account the effects of speaking rate on the phonetic unit durational parameters, two durational models are proposed. The ways those models are integrated in the recognition processing are described. Experiments on a French number database show that such an explicit introduction of prosodic parameters reduces recognition errors rates by 20%
Keywords :
hidden Markov models; signal representation; spectral analysis; speech recognition; French number database; acoustic information; global sound duration; phonetic unit durational parameters; prosodic features; recognition error rates; recognition processing; representation; speaking rate; spectral features; speech recognition system; suprasegmental information; two level HMM; Databases; Error analysis; Hidden Markov models; Histograms; Network topology; Probability distribution; Solid modeling; Speech processing; Speech recognition; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
ISSN :
1520-6149
Print_ISBN :
0-7803-1775-0
Type :
conf
DOI :
10.1109/ICASSP.1994.389354
Filename :
389354
Link To Document :
بازگشت