Lyon's auditory features and MRAM features comparison for non-intrusive speech quality assessment in narrowband speech

Abstract

Lyon's auditory features and Multi-Resolution Auditory Model (MRAM) features for narrowband speech sampled at 8 kHz for different degradations are computed. The Gaussian Mixture Model (GMM) has been used to map these auditory features of narrowband speech into the objective mean opinion score (MOS) using Expectation Maximization (EM) algorithm. Non-intrusive speech quality assessment has been done using Lyon's auditory features and MRAM features and their efficacy has been compared in terms of the correlation coefficients between the subjective MOS and the computed objective MOS. The results in terms of root mean square error (RMSE) between the subjective MOS and the computed objective MOS are computed and compared. The results in terms of the correlation coefficients are also compared with ITU-T Recommendation P.563, a standard for non-intrusive speech quality assessment, on ITU-T supplement-23, NOIZEUS-960 and NOIZEUS-2240 databases.