An Instrumental Intelligibility Metric Based on Information Theory

We propose a monaural intrusive instrumental intelligibility metric called speech intelligibility in bits (SIIB). SIIB is an estimate of the amount of information shared between a talker and a listener in bits per second. Unlike existing information theoretic intelligibility metrics, SIIB accounts f...

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Veröffentlicht in:IEEE signal processing letters 2018-01, Vol.25 (1), p.115-119
Hauptverfasser: Van Kuyk, Steven, Kleijn, W. Bastiaan, Hendriks, Richard C.
Format: Artikel
Sprache:eng
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Zusammenfassung:We propose a monaural intrusive instrumental intelligibility metric called speech intelligibility in bits (SIIB). SIIB is an estimate of the amount of information shared between a talker and a listener in bits per second. Unlike existing information theoretic intelligibility metrics, SIIB accounts for talker variability and statistical dependencies between time-frequency units. Our evaluation shows that relative to state-of-the-art intelligibility metrics, SIIB is highly correlated with the intelligibility of speech that has been degraded by noise and processed by speech enhancement algorithms.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2017.2774250