Objective Intelligibility Prediction of Speech by Combining Correlation and Distortion based Techniques
MetadataShow full item record
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.
12thAnnual Conference of the International Speech Communication Association
Copyright 2011 ISCA and the Authors. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference’s website or contact the authors.
Artificial Intelligence and Image Processing not elsewhere classified