Title :
A new strategy of fuzzy-neural network for Thai numeral speech recognition
Author :
Wutiwiwatchai, C. ; Jitapunkul, S. ; Arkuputra, V. ; Maneenoi, E. ; Amornkul, P. ; Luksaneeyanawin, S.
Author_Institution :
Digital Signal Process. Res. Lab, Chulalongkorn Univ., Bangkok, Thailand
Abstract :
Instead of using the fuzzy membership input with class membership desired output among training procedures as proposed by several researchers, we used the fuzzy membership input with conventional binary desired output. This can reduce the mistaken training, decrease the training time and also improve the recognition ability. The system was tested on the recognition of ten Thai numerals from zero to nine. The error rate for speaker-independent tests achieved 9.2% compared with 14% error rate for conventional neural network systems while the error rate of the system using class membership desired output is somewhat higher because of mistaken training
Keywords :
fuzzy neural nets; speech recognition; Thai numeral; binary desired output; fuzzy membership input; fuzzy-neural network; recognition ability; speaker-independent tests; speech recognition; training time; Electronic mail; Error analysis; Feature extraction; Fuzzy neural networks; Fuzzy systems; Humans; Linear predictive coding; Neural networks; Speech recognition; System testing;
Conference_Titel :
Circuits and Systems, 1998. IEEE APCCAS 1998. The 1998 IEEE Asia-Pacific Conference on
Conference_Location :
Chiangmai
Print_ISBN :
0-7803-5146-0
DOI :
10.1109/APCCAS.1998.743701