DocumentCode
1319250
Title
Hidden Markov models with duration-dependent state transition probabilities (speech recognition)
Author
Vaseghi, S.V.
Author_Institution
East Anglia Univ., Norwich, UK
Volume
27
Issue
8
fYear
1991
fDate
4/11/1991 12:00:00 AM
Firstpage
625
Lastpage
626
Abstract
A new method is proposed for incorporation of duration knowledge in the form of duration-dependent state transition probabilities in a left-right hidden Markov model. Duration-dependent transition probabilities are derived from integration of histograms of the state durations. The model re-estimation process becomes one of obtaining a new segmentation from which a new set of state and observation probabilities are derived.
Keywords
Markov processes; probability; speech recognition; duration knowledge; duration-dependent state transition probabilities; histogram integration; left-right hidden Markov model; model re-estimation process; segmentation; speech recognition;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19910392
Filename
83273
Link To Document