DocumentCode :
2279214
Title :
Continuous multi-band speech recognition using Bayesian networks
Author :
Daoudi, Khalid ; Fohr, Dominique ; Antoine, Christophe
Author_Institution :
INRIA-LORIA, Villers les Nancy, France
fYear :
2001
fDate :
2001
Firstpage :
41
Lastpage :
44
Abstract :
Using the Bayesian networks framework, we present a new multi-band approach for continuous speech recognition. This new approach has the advantage of overcoming all the limitations of the standard multi-band techniques. Moreover, it leads to a higher fidelity speech modeling than HMMs. We provide a preliminary evaluation of the performance of our new approach on a connected digits recognition task.
Keywords :
belief networks; parameter estimation; speech recognition; Bayesian networks; HMM; connected digits recognition; continuous speech recognition; model parameters estimation; multi-band speech recognition; Automatic speech recognition; Bayesian methods; Decoding; Hidden Markov models; Random variables; Speech recognition; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Speech Recognition and Understanding, 2001. ASRU '01. IEEE Workshop on
Print_ISBN :
0-7803-7343-X
Type :
conf
DOI :
10.1109/ASRU.2001.1034584
Filename :
1034584
Link To Document :
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