A Novel Approach for Auditory Spectrum Enhancement to Improve Speech Recognition's Robustness

被引：0
|
作者：
Salhi, Khaireddine [1 ]
Hajaiej, Zied [1 ]
Ellouze, Noureddine [1 ]
机构：
[1] Natl Engn Sch Tunis ENIT, LSITI, BP 37, Tunis 1002, Tunisia
来源：
2015 IEEE 12TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD) | 2015年
关键词：
Gammachirp; Wavelet Transform; Hidden Markov Models; Mel-Frequency Cepestral Coefficients; FILTER SHAPES; PLP;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The success of acoustic features derived from MFCC and PLP turned them into a standard choice in specific conditions but their performances degrade with additive noise. Recently, we have proposed an auditory feature extractor based on gammachirp wavelet transform, they are obtained by replacement of the filter bank used in above methods by a gammachirp wavelet transform. We found that proposed feature give a significant improvement in robust speech recognition than conventional acoustic feature.
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页数：5
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