Speech Intelligibility Prediction Based on Mutual Information

Jesper Jensen, Cees H. Taal

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

44 Citationer (Scopus)
1418 Downloads (Pure)

Abstract

This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting the intelligibility of speech signals contaminated by additive noise and potentially non-linearly processed using time-frequency weighting.
OriginalsprogEngelsk
TidsskriftI E E E Transactions on Audio, Speech and Language Processing
Vol/bind22
Udgave nummer2
Sider (fra-til)430-440
ISSN1558-7916
DOI
StatusUdgivet - feb. 2014

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