DocumentCode
3026146
Title
Fuzzy hidden Markov models for speech and speaker recognition
Author
Tran, Dat ; Wagner, Michael
Author_Institution
Sch. of Comput., Canberra Univ., Belconnen, ACT, Australia
fYear
1999
fDate
36342
Firstpage
426
Lastpage
430
Abstract
The paper proposes a fuzzy approach to the hidden Markov model (HMM) method called the fuzzy HMM for speech and speaker recognition. The fuzzy HMM algorithm is regarded as an application of the fuzzy expectation-maximisation (EM) algorithm to the Baum-Welch algorithm in the HMM. Speech and speaker recognition experiments using the Texas Instruments (TI46) speech data corpus show better results for fuzzy HMMs compared with conventional HMMs
Keywords
fuzzy set theory; hidden Markov models; natural languages; optimisation; speaker recognition; Baum-Welch algorithm; Texas Instruments speech data corpus; fuzzy HMM algorithm; fuzzy approach; fuzzy expectation-maximisation algorithm; fuzzy hidden Markov models; speaker recognition; Australia; Clustering algorithms; Extraterrestrial measurements; Hidden Markov models; Instruments; Iterative algorithms; Probability density function; Speaker recognition; Speech recognition; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
Conference_Location
New York, NY
Print_ISBN
0-7803-5211-4
Type
conf
DOI
10.1109/NAFIPS.1999.781728
Filename
781728
Link To Document