DocumentCode
1354463
Title
Influence of initialisation and stop criteria on HMM based recognisers
Author
Ferrer, M.A. ; Alonso, I.G. ; Travieso, C.M.
Author_Institution
Dept. de Senales y Comunicaciones, Univ. de las Palmas de Grun Canaria, Spain
Volume
36
Issue
13
fYear
2000
fDate
6/22/2000 12:00:00 AM
Firstpage
1165
Lastpage
1166
Abstract
A study is presented into the importance of two commonly overlooked factors influencing generalisation ability in the field of hidden Markov model (HMM) based recogniser training algorithms by means of a comparative study of four initialisation methods and three stop criteria in different applications. The results show that better results have been found with the equal-occupancy initialisation method and the fixed-threshold stop criterion
Keywords
generalisation (artificial intelligence); hidden Markov models; learning (artificial intelligence); speech recognition; HMM based recognisers; equal-occupancy initialisation method; fixed-threshold stop criterion; generalisation ability; initialisation; speech recognition; training algorithms;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:20000826
Filename
850484
Link To Document