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Updated: May 27, 2026

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Published on: September 27, 2024
An evaluation of objective measures for intelligibility prediction of time-frequency weighted noisy speech
Cees H Taal1, Richard C Hendriks, Richard Heusdens
1Delft, University of Technology, 2628 CD Delft, The Netherlands. c.h.taal@tudelft.nl
Abstract:
Existing objective speech-intelligibility measures are suitable for several types of degradation, however, it turns out that they are less appropriate in cases where noisy speech is processed by a time-frequency weighting. To this end, an extensive evaluation is presented of objective measure for intelligibility prediction of noisy speech processed with a technique called ideal time frequency (TF) segregation. In total 17 measures are evaluated, including four advanced speech-intelligibility measures (CSII, CSTI, NSEC, DAU), the advanced speech-quality measure (PESQ), and several frame-based measures (e.g., SSNR). Furthermore, several additional measures are proposed. The study comprised a total number of 168 different TF-weightings, including unprocessed noisy speech. Out of all measures, the proposed frame-based measure MCC gave the best results (ρ = 0.93). An additional experiment shows that the good performing measures in this study also show high correlation with the intelligibility of single-channel noise reduced speech.
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