Feature extraction based on auditory representations for robust speech recognition

Abstract

A computational auditory model based on the detection of zero-crossings is introduced for robust speech recognition. The proposed method not only preserves intensity information, but is also robust to noise in frequency estimation. The robustness of the proposed method is verified analytically and experimentally.