A new mask-based objective measure for predicting the intelligibility of binary masked speech

Yu, Chengzhu; Wójcicki, Kamil; Loizou, Philip C.; Hansen, John H. L.

doi:10.1109/icassp.2013.6639025

Cited by 2 publications

(1 citation statement)

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“…However, a number of studies have shown that each T-F unit has a different perceptual effect depending on its intensity (Zhang et al, 2001;Yu et al, 2013) as well as different acoustic correlates Allen, 2009, 2011). To the best of our knowledge, no studies have yet assessed the relative contribution of individual T-F units to speech intelligibility in the context of speech separation in noise.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the importance of time-frequency contributions to speech intelligibility in noise

Wójcicki

Loizou

et al. 2014

The Journal of the Acoustical Society of America

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Recent studies on binary masking techniques make the assumption that each time-frequency (T-F) unit contributes an equal amount to the overall intelligibility of speech. The present study demonstrated that the importance of each T-F unit to speech intelligibility varies in accordance with speech content. Specifically, T-F units are categorized into two classes, speech-present T-F units and speech-absent T-F units. Results indicate that the importance of each speech-present T-F unit to speech intelligibility is highly related to the loudness of its target component, while the importance of each speech-absent T-F unit varies according to the loudness of its masker component. Two types of mask errors are also considered, which include miss and false alarm errors. Consistent with previous work, false alarm errors are shown to be more harmful to speech intelligibility than miss errors when the mixture signal-to-noise ratio (SNR) is below 0 dB. However, the relative importance between the two types of error is conditioned on the SNR level of the input speech signal. Based on these observations, a mask-based objective measure, the loudness weighted hit-false, is proposed for predicting speech intelligibility. The proposed objective measure shows significantly higher correlation with intelligibility compared to two existing mask-based objective measures.

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Section: Introductionmentioning

confidence: 99%