Technical Program

Paper Detail

Paper:	SLP-P21.6
Session:	Speech Detection, Enhancement and Analysis
Time:	Friday, May 19, 16:30 - 18:30
Presentation:	Poster
Topic:	Speech and Spoken Language Processing: Speech Analysis
Title:	Assessment of Objective Quality Measures for Speech Intelligibility Estimation
Authors:	Wei Ming Liu, University of Wales Swansea, United Kingdom; Keith A Jellyman, Swansea University, United Kingdom; John S. D. Mason, Nicholas W. D. Evans, University of Wales Swansea, United Kingdom
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 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 con£gurations of the new codec, while most others fail.