Speech recognition using a wavelet packet adaptive network based fuzzy inference system

被引:75
作者
Avci, Engin [1 ]
Akpolat, Zuhtu Hakan [1 ]
机构
[1] Firat Univ, Dept Elect & Comp Sci, Elazig 23119, Turkey
关键词
wavelet packet adaptive network based fuzzy inference system; speech recognition; speech/voice signal; feature extraction; wavelet packet decomposition; entropy; expert system;
D O I
10.1016/j.eswa.2005.09.058
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, an expert speech recognition system is presented. This paper especially deals with the combination of feature extraction and classification for real speech signals. A Wavelet packet adaptive network based fuzzy inference system (WPANFIS) model is developed in this study. WPANFIS consists of two layers: wavelet packet and adaptive network based fuzzy inference system. The wavelet packet layer is used for adaptive feature extraction in the time-frequency domain and is composed of wavelet packet decomposition and wavelet packet entropy. The performance of the developed system is evaluated by using noisy speech signals. Test results showing the effectiveness of the proposed speech recognition system are presented in the paper. The rate of correct classification is about 92% for the sample speech signals. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:495 / 503
页数:9
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