International Journal of Science and Technology

International Journal of Science and Technology>> Volume 7, Number 9, September 2017

International Journal of Science and Technology

Evaluation of Different Feature Extraction Techniques for Continuous Speech Recognition

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Author Hamdy K. Elminir, Mohamed Abu ElSoud, L. M. Abou El-Maged
On Pages 689-695
Volume No. 2
Issue No. 10
Issue Date October, 2012
Publishing Date October, 2012
Keywords Mel-frequency cepstral coefficients (MFCC); Linear predictive coding (LPC); Zero Crossings with Peak Amplitudes (ZCPA); Hidden Markov Model(HMM);principal component analysis(PCA)


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.

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