Comparison of auditory models for robust speech recognition

Abstract

Two auditory front ends which emulate some aspects of the human auditory system were compared using a high performance isolated word Hidden Markov Model (HMM) speech recognizer. In these initial studies, auditory models from Seneff [2] and Ghitza [4] were compared using both clean speech and speech corrupted by speech-like "babble" noise. Preliminary results indicate that the auditory models reduce the error rate slightly, especially at intermediate and high noise levels.