Abstract

To achieve robust distant-talking automatic speech recognition in reverberant environments, the effect of reverberation on the speech feature sequences has to be modeled as accurately as possible. A convolution in the feature domain has been proposed recently in [1, 2, 3, 4] to capture the dispersion of the feature vectors caused by reverberation. These publications use a fixed representation of the acoustic path between speaker and microphone or an elementary statistical reverberation model based on simplifying assumptions. In this contribution, we propose a Monte-Carlo approach that allows for an explicit determination of the joint probability density function of a feature-domain reverberation model. Index Terms — Robust speech recognition, distant-talking speech recognition, reverberation modeling, feature-domain processing, Monte-Carlo method 1.

Citations