A new strategy of fuzzy-neural network for Thai numeral speech recognition

被引：1

作者：

Wutiwiwatchai, C ^{[1
]}

Jitapunkul, S ^{[1
]}

Arkuputra, V ^{[1
]}

Maneenoi, E ^{[1
]}

Amornkul, P ^{[1
]}

Luksaneeyanawin, S ^{[1
]}

机构：

[1] Chulalongkorn Univ, Fac Engn, Dept Elect Engn, Digital Signal Proc Res Lab, Bangkok 10330, Thailand

来源：

APCCAS '98 - IEEE ASIA-PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS: MICROELECTRONICS AND INTEGRATING SYSTEMS | 1998年

关键词：

D O I：

10.1109/APCCAS.1998.743701

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this research, a new strategy of Fuzzy-Neural Network system was proposed for Thai numeral speech recognition. Instead of using the fuzzy membership input with class membership desired output among training procedure as proposed by several researches, 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 test achieved 9.2% compared with 14% error rate of conventional neural network system while the error rate of the system using class membership desired output is somewhat high because of mistaken training.

引用

页码：161 / 164

页数：4

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