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Power-normalized PLP (PNPLP) feature for robust speech recognition

In this paper, we first review several approaches of feature extraction algorithms in robust speech recognition, e.g. Mel frequency cepstral coefficients (MFCC) [1], perceptual linear prediction (PLP) [2] and power-normalized cepstral coefficients (PNCC) [3]. A new feature extraction algorithm for noise robust speech recognition is proposed, in which medium-time processing works as noise suppression module. The details will be described to show that the algorithm is superior. The experimental results prove that our proposed method significantly outperforms state-of-the-art algorithms.