Speech quality estimation using Gaussian mixture models
Tiago Henrique Falk, Wai-Yip Chan, P. Kabal · 2004
Abstract—An algorithm for nonintrusive speech quality esti-mation based on Gaussian mixture models (GMMs) is presented. GMMs are used to form an artificial reference model of the behavior of features of undegraded speech. Consistency measures between the degraded speech signal and the reference model serve as indicators of speech quality. Consistency values are mapped to an objective speech quality score using a multivariate adaptive regression splines function. When tested on unseen data, the proposed algorithm generally outperforms ITU-T standard P.563, which is the current “state-of-the-art ” algorithm. The algorithm computes objective quality scores roughly twice as fast as P.563. Index Terms—Gaussian mixtures, quality assurance, quality measurement, quality of service, speech coding, speech quality, speech transmission, telephony. I.