Reverberation and Noise Robust Feature Compensation Based on IMM

Abstract

In this paper, we propose a novel feature compensation approach based on the interacting multiple model (IMM) algorithm specially designed for joint processing of background noise and acoustic reverberation. Our approach to cope with the time-varying environmental parameters is to establish a switching linear dynamic model for the additive and convolutive distortions, such as the background noise and acoustic reverberation, in the log-spectral domain. We construct multiple state space models with the speech corruption process in which the log spectra of clean speech and log frequency response of acoustic reverberation are jointly handled as the state of our interest. The proposed approach shows significant improvements in the Aurora-5 automatic speech recognition (ASR) task which was developed to investigate the influence on the performance of ASR for a hands-free speech input in noisy room environments.