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
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;
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
DOI :
10.1109/NAFIPS.1999.781728
