Objective speech quality assessment with non-intrusive method for narrowband speech

Jing Wang*, Juan Luo, Shenghui Zhao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

A non-intrusive objective assessment method is proposed to estimate the quality of output speech without the input reference speech based on narrowband speech test database. From clean speech Perceptual Linear Predictive (PLP) features are extracted and clustered by Gaussian Mixture Model (GMM) as an artificial reference model. Input speech is separated into three classes, for which the consistency measures between features of the test speech signal and the GMM reference model are calculated and mapped to an objective speech quality score using Support Vector Regression (SVR) method. Experiment results show that the proposed method has a higher objective to subjective correlation degree than ITU-T P.563 within 6 narrowband MOS- labeled test databases.

Original languageEnglish
Title of host publication2008 9th International Conference on Signal Processing, ICSP 2008
Pages518-521
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 9th International Conference on Signal Processing, ICSP 2008 - Beijing, China
Duration: 26 Oct 200829 Oct 2008

Publication series

NameInternational Conference on Signal Processing Proceedings, ICSP

Conference

Conference2008 9th International Conference on Signal Processing, ICSP 2008
Country/TerritoryChina
CityBeijing
Period26/10/0829/10/08

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