SII-Based Speech Prepocessing for Intelligibility Improvement in Noise

Cees H. Taal, Jesper Jensen

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A linear time-invariant filter is designed in order to improve speech understanding when the speech is played back in a noisy environment. To accomplish this, the speech intelligibility index (SII) is maximized under the constraint that the speech energy is held constant. A nonlinear approximation is used for the SII such that a closed-form solution exists to the constrained optimization problem. The resulting filter is dependent both on the long-term average noise and speech spectrum and the global SNR and, in general, has a high-pass characteristic. In contrast to existing methods, the proposed filter sets certain frequency bands to zero when they do not contribute to intelligibility anymore. Experiments show large intelligibility improvements with the proposed method when used in stationary speech-shaped noise. However, it was also found that the method does not perform well for speech corrupted by a competing speaker. This is due to the fact that the SII is not a reliable intelligibility predictor for fluctuating noise sources. MATLAB code is provided.
Original languageEnglish
JournalProceedings of the International Conference on Spoken Language Processing
Pages (from-to)3582-3586
Number of pages6
Publication statusPublished - 2013
EventInterspeech 2013 - Lyon, France
Duration: 25 Aug 201329 Aug 2013


ConferenceInterspeech 2013
Internet address


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