Robust speech recognition techniques using a radial basis function neural network for mobile applications

被引：0
|
作者：
Sankar, R
Sethi, NS
机构：
来源：
IEEE SOUTHEASTCON '97 - ENGINEERING THE NEW CENTURY, PROCEEDINGS | 1996年
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D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we present the development of robust speech recognition techniques for voice activated dialing (VAD) for cellular phone in a car. Noise seduction techniques are implemented before modeling the speech parameters in the homomorphic domain. The FFT derived cepstral coefficients are liftered and then Mel-scale warped to generate the feature vector. Radial Basis Function Neural Network is used as final classifier and variation in its structure is studied to evaluate its real-time performance, Results on speaker-dependent and speaker-independent recognition across -5 dB to 25 dB SNR range are presented and a performance evaluation is carried out for different front-end techniques. The system is evaluated using NOISEX-92 database.
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页码：87 / 91
页数：5
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