Objective Intelligibility Prediction of Speech by Combining Correlation and Distortion based Techniques

Abstract

A number of techniques based on correlation measurements have recently been proposed to provide an objective measure of intelligibility. These techniques are able to detect nonlinear distortions and provide intelligibility scores highly correlated with those given by human listeners. However, the performance of these techniques has not been found satisfactory for measuring the speech intelligibility of speech enhancement algorithms. In this paper we first investigate the different correlation-based methods, in the context of speech enhancement. We then propose to combine these correlation-based techniques with spectral distance based ones. Results presented show that objective intelligibility prediction is significantly improved by this combination.