Enhanced Non-Intrusive Speech Quality Measurement Using Degradation Models

Abstract

The speech quality estimation scheme in [1] is improved with the addition of a reference model of the behavior of speech degraded by different transmission and/or coding schemes. Moreover, via maximization of a mutual information measure, we validate the use of segmental SNR as a measure of the amount of multiplicative noise present in the test signal. These two additions result in an algorithm that is more accurate and more robust to certain distortion conditions. When tested on unseen data, the proposed algorithm outperforms the current "state-of- art" P.563 algorithm while requiring considerably lower computational complexity.