Phase Spectra Based Feature for Robust Speech Recognition

Abstract

Speech recognition in adverse environment is one of the major issue in automatic speech recognition nowadays. While most current speech recognition system show to be highly efficient for ideal environment but their performance go down extremely when they are applied in real environment because of noise effected speech. In this paper a new feature representation based on phase spectra and Perceptual Linear Prediction (PLP) has been suggested which can be used for robust speech recognition. It is shown that this new features can improve the performance of speech recognition not only in clean condition but also in various levels of noise condition when it is compared to PLP features.