Speech quality objective assessment using neural network

This paper presents a novel method for objective assessment of speech quality based on one-step strategy using a feedfoward neutral network. Currently, almost all the existing methods for this assessment can be regarded as a two-step strategy, requiring a distortion computation and a mapping from th...

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Published in2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100) Vol. 3; pp. 1511 - 1514 vol.3
Main Authors Qiang Fu, Kechu Yi, Mingui Sun
Format Conference Proceeding
LanguageEnglish
Published IEEE 2000
Subjects
Auditory system
Distortion measurement
Humans
Laboratories
Neural networks
Nonlinear distortion
Quality assessment
Regression analysis
Speech analysis
Testing
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Summary:This paper presents a novel method for objective assessment of speech quality based on one-step strategy using a feedfoward neutral network. Currently, almost all the existing methods for this assessment can be regarded as a two-step strategy, requiring a distortion computation and a mapping from the average distortion value to the mean opinion score (MOS). Our new method combines these two steps by means of a neural network which can incorporate the perception properties of the human auditory system and provide an MOS estimate directly. Our theoretical analysis and experimental results suggest that this method of MOS estimate significantly overperforms the traditional methods. The correlation coefficient between the subjective test score and objective MOS estimate can reach up to about 0.95.
ISBN:9780780362932
0780362934
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2000.861932