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

Abstract

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.