文章基本信息

标题：Evaluation of Different Feature Extraction Techniques for Continuous Speech Recognition
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作者：Hamdy K. Elminir ; Mohamed Abu ElSoud ; L. M. Abou El-Maged 等
期刊名称：International Journal of Information and Communication Technology Research
电子版ISSN：2223-4985
出版年度：2012
卷号：2
期号：12
出版社：IRPN Publishers
摘要：Extracting human's voice feature is the most important process in any speech recognition system. There are many feature extraction techniques which are already used such as MFCC, LPC and ZCPA; but still have some problems especially in the continuous speech. It is important to evaluate different feature extraction techniques for continuous speech by making a comparison between these techniques as a trial to find the most suitable technique for speech recognition process, and trying to enhance the result by using PCA. Using PCA gives great better results especially for ZCPA technique as a comparison to other techniques.
关键词：Mel-frequency cepstral coefficients (MFCC); Linear predictive coding (LPC); Zero Crossings with Peak Amplitudes (ZCPA); Hidden Markov Model(HMM);principal component analysis(PCA)