Hybrid HMM/DTW based Speech Recognition with Kernel Adaptive Filtering Method

Cyril Onwubiko, K. Ouazzane
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引用次数: 3

Abstract

We have proposed new approach for the speech recognition system by applying kernel adaptive filterfor speech enhancement and for the recognition,the hybrid HMM/DTW methods are usedin this paper. Noise removal is very important in many applications like telephone con versation, speech recognition, etc.In the recent past, the kernel methods are showing good results for speech processing applications . The feature used in the recognition process is MFCC features. It consists of a HMM system used to trainthe speech features and for classification purpose used the DTW method. Experimental results show a relative improvementof recognition rate compared to the traditional methods.
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基于核自适应滤波的混合HMM/DTW语音识别方法
本文提出了一种新的语音识别方法,将核自适应滤波器用于语音增强,将HMM/DTW混合方法用于语音识别。在电话通话、语音识别等许多应用中,噪声的去除是非常重要的。近年来,核方法在语音处理应用中显示出良好的效果。识别过程中使用的特征是MFCC特征。它由HMM系统组成,用于训练语音特征,并使用DTW方法进行分类。实验结果表明,与传统方法相比,该方法的识别率有了一定的提高。
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International Journal of Computer Science and Applications
International Journal of Computer Science and Applications Computer Science-Computer Science Applications
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期刊介绍: IJCSA is an international forum for scientists and engineers involved in computer science and its applications to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the IJCSA are selected through rigorous peer review to ensure originality, timeliness, relevance, and readability.
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