DocumentCode :
1711476
Title :
Use of a novel generalized fuzzy hidden Markov model for speech recognition
Author :
Cheok, Adrian David ; Chevalier, Sylvain ; Kaynak, Mustafa ; Sengupta, Kuntal ; Chung, KO Chi
Author_Institution :
Nat. Univ. of Singapore, Singapore
Volume :
3
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
1207
Lastpage :
1210
Abstract :
We discuss a type of hidden Markov model (HMM) based on fuzzy sets and fuzzy integral theory which generalizes the classical stochastic HMM. The Choquet integral is used as a fuzzy integral which relaxes one of the two independence assumptions that we had with the classical HMM. We apply this new model to speech recognition and compare the performance with the classical HMM. In this research, the main innovation is that this new generalized fuzzy HMM is applied for the first time to speech recognition. Due to the fuzziness of the model, an interesting gain can be observed in terms of a lower computation time
Keywords :
fuzzy set theory; hidden Markov models; integral equations; probability; speech recognition; Choquet integral; computation time; fuzzy integral; fuzzy integral theory; fuzzy sets; generalized fuzzy hidden Markov model; independence assumptions; speech recognition; Fuzzy logic; Fuzzy sets; Hidden Markov models; Neural networks; Particle measurements; Robustness; Search problems; Speech recognition; Stochastic processes; Technological innovation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-7293-X
Type :
conf
DOI :
10.1109/FUZZ.2001.1008874
Filename :
1008874
Link To Document :
بازگشت