Paper Info
Title
Assessment Of Objective Quality Measures For Speech Intelligibility Estimation
Abstract
This paper investigates the accuracy of automatic speech recognition (ASR) and 6 other well-reported objective quality measures for the task of estimating speech intelligibility. It is believed to be the first assessment of such a range of measures side-by-side and in the context of intelligibility. A total of 39 degradation conditions including those from a newly proposed low bit rate (0.3 to 1.5kbps) codec and a noise suppression system are considered. They provide real and varied scenarios to assess the measures. The objective scores are compared to subjective listening scores, and their correlation used to assess the approach. All tests are conducted on the European standard Aurora 2 corpus. Experiments show that ASR and perceptual estimation of speech quality (PESQ) are potentially reliable estimators of intelligibility with subjective correlation as high as 0.99 and 0.96 respectively. Furthermore, ASR gives a trend corresponding to that of subjective intelligibility assessment for the different configurations of the new codec, while most others fail.
Year
DOI
Venue
2006
10.1109/ICASSP.2006.1660248
2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13
Keywords
Field
DocType
artificial intelligence,codecs,speech intelligibility,speech recognition,degradation,speech coding,automatic speech recognition,testing,codec
Speech coding,European standard,Computer science,Active listening,Speech recognition,Correlation,Codec,Intelligibility (communication),Estimator,PESQ
Conference
ISSN
Citations 
PageRank 
1520-6149
3
0.46
References 
Authors
4
4
Name
Order
Citations
PageRank
Wei Ming Liu1233.89
Keith A. Jellyman251.19
John S. D. Mason321318.22
nicholas evans459454.41