Enhanced Perceptual Model For Non-Intrusive Speech Quality Assessment

Author

Kim, Doh-Suk ; Tarraf, Ahmed

Author_Institution

Lucent Technol., Whippany, NJ

Volume

1

fYear

2006

fDate

14-19 May 2006

Abstract

In this paper, we propose a novel model for estimating the quality of speech without the reference speech information. The proposed auditory non-intrusive quality estimation plus (ANIQUE+) model is a perceptual model simulating the functional role of human auditory system, and employs improved modeling of quality estimation by statistical learning methods. Experimental evaluation demonstrated that the performance of the ANIQUE+ model is significantly superior to that of the current ITU-T standard recommendation P.563 on 34 different subjective mean opinion score (MOS) databases - the averaged correlation between subjective and objective quality scores is about 0.97 for ANIQUE+, whereas P.563 shows 0.87 averaged correlation

Keywords

learning (artificial intelligence); speech enhancement; statistical analysis; ANIQUE+; auditory nonintrusive quality estimation plus; enhanced perceptual model; human auditory system; mean opinion score databases; nonintrusive speech quality assessment; statistical learning methods; Auditory system; Databases; Degradation; Distortion; Filter bank; Humans; Quality assessment; Speech enhancement; Statistical learning; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1660149

Filename

1660149