On the Use of Different Feature Extraction Methods for Linear and Non Linear kernels

27 Jun 2014 Imen Trabelsi Dorra Ben Ayed

The speech feature extraction has been a key focus in robust speech recognition research; it significantly affects the recognition performance. In this paper, we first study a set of different features extraction methods such as linear predictive coding (LPC), mel frequency cepstral coefficient (MFCC) and perceptual linear prediction (PLP) with several features normalization techniques like rasta filtering and cepstral mean subtraction (CMS)... (read more)

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