DocumentCode :
312147
Title :
Mixture splitting technique and temporal control in a HMM-based recognition system
Author :
Montacié, C. ; Caratay, M.-J. ; Barras, C.
Author_Institution :
Paris VI Univ., France
Volume :
2
fYear :
1996
fDate :
3-6 Oct 1996
Firstpage :
977
Abstract :
Studies various techniques to improve the performance and to reduce the computation cost and the required memory of a speech recognition system based on hidden Markov models (HMMs). For the efficiency of the system, we first study the optimization of the number of HMM parameters according to training data. We experiment with the temporal control of the phonetic transitions on a lexical decoding task with a significant 5% improvement. Finally, a preliminary method for dynamically selecting a sublexicon is studied in order to reduce the lexical decoding cost
Keywords :
Gaussian distribution; decoding; hidden Markov models; optimisation; software performance evaluation; speech recognition; HMM parameter optimization; computation cost; dynamic sublexicon selection; efficiency; hidden Markov models; lexical decoding cost; lexical decoding task; mixture splitting technique; performance; phonetic transitions; required memory; speech recognition system; temporal control; training data; Computational efficiency; Control systems; Costs; Databases; Decoding; Frequency estimation; Gaussian distribution; Hidden Markov models; Probability density function; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-3555-4
Type :
conf
DOI :
10.1109/ICSLP.1996.607766
Filename :
607766
Link To Document :
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