DocumentCode
908670
Title
Robust parametric modeling of durations in hidden Markov models
Author
Burshtein, David
Author_Institution
Dept. of Electr. Eng.-Syst., Tel Aviv Univ., Israel
Volume
4
Issue
3
fYear
1996
fDate
5/1/1996 12:00:00 AM
Firstpage
240
Lastpage
242
Abstract
A major weakness of conventional hidden Markov models is that they implicitly model state durations by a geometric distribution, which is usually inappropriate. This paper presents a modified Viterbi algorithm that, by incorporating proper state and word duration modeling, significantly reduces the string error rate of the conventional Viterbi algorithm for a speaker-independent, connected-digit string task. The algorithm has essentially the same computational requirements of the conventional Viterbi algorithm
Keywords
hidden Markov models; maximum likelihood estimation; speech recognition; string matching; HMM; hidden Markov models; modified Viterbi algorithm; robust parametric modeling; speaker-independent connected-digit string task; speech recognition; state duration modeling; string error rate; word duration modeling; Error analysis; Exponential distribution; Hidden Markov models; Parametric statistics; Probability distribution; Robustness; Solid modeling; Speech recognition; State estimation; Viterbi algorithm;
fLanguage
English
Journal_Title
Speech and Audio Processing, IEEE Transactions on
Publisher
ieee
ISSN
1063-6676
Type
jour
DOI
10.1109/89.496221
Filename
496221
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