DocumentCode
1171022
Title
Hierarchical phoneme recognition by hidden Markov models based on multiple feature integration
Author
Ariki, Y. ; McInnes, F.R. ; Jack, M.A.
Author_Institution
Edinburgh Univ., UK
Volume
25
Issue
14
fYear
1989
fDate
7/6/1989 12:00:00 AM
Firstpage
918
Lastpage
919
Abstract
A method of hierarchical phoneme recognition which utilises the most selective features for each individual phoneme is reported. Input speech patterns are classified into broad classes on the basis of LPC-derived cepstral data. Then, the speech is further classified to a fine-class level using mel-formant data for vowel models only. Hidden Markov models (HMM) are used at both levels of classification.
Keywords
speech analysis and processing; speech recognition; LPC-derived cepstral data; broad classes; fine-class level; hidden Markov models; hierarchical phoneme recognition; levels of classification; multiple feature integration; speech patterns; vowel models;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19890615
Filename
31938
Link To Document