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Binary Mask

The Experts below are selected from a list of 6021 Experts worldwide ranked by ideXlab platform

Mike Brookes – 1st expert on this subject based on the ideXlab platform

  • Improving the perceptual quality of ideal Binary Masked speech
    2017 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2017
    Co-Authors: Leo Lightburn, Enzo De Sena, Alastair Moore, Patrick A. Naylor, Mike Brookes

    Abstract:

    It is known that applying a time-frequency Binary Mask to very noisy speech can improve its intelligibility but results in poor perceptual quality. In this paper we propose a new approach to applying a Binary Mask that combines the intelligibility gains of conventional Binary Masking with the perceptual quality gains of a classical speech enhancer. The Binary Mask is not applied directly as a time-frequency gain as in most previous studies. Instead, the Mask is used to supply prior information to a classical speech enhancer about the probability of speech presence in different time-frequency regions. Using an oracle ideal Binary Mask, we show that the proposed method results in a higher predicted quality than other methods of applying a Binary Mask whilst preserving the improvements in predicted intelligibility.

  • SOBM – a Binary Mask for noisy speech that optimises an objective intelligibility metric
    2015 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2015
    Co-Authors: Leo Lightburn, Mike Brookes

    Abstract:

    It is known that the intelligibility of noisy speech can be improved by applying a Binary-valued gain Mask to a time-frequency representation of the speech. We present the SOBM, an oracle Binary Mask that maximises STOI, an objective speech intelligibility metric. We show how to determine the SOBM for a deterministic noise signal and also for a stochastic noise signal with a known power spectrum. We demonstrate that applying the SOBM to noisy speech results in a higher predicted intelligibility than is obtained with other Masks and show that the stochastic version is robust to mismatch errors in SNR and noise spectrum.

  • ICASSP – SOBM – a Binary Mask for noisy speech that optimises an objective intelligibility metric
    2015 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2015
    Co-Authors: Leo Lightburn, Mike Brookes

    Abstract:

    It is known that the intelligibility of noisy speech can be improved by applying a Binary-valued gain Mask to a timefrequency representation of the speech. We present the SOBM, an oracle Binary Mask that maximises STOI, an objective speech intelligibility metric. We show how to determine the SOBM for a deterministic noise signal and also for a stochastic noise signal with a known power spectrum. We demonstrate that applying the SOBM to noisy speech results in a higher predicted intelligibility than is obtained with other Masks and show that the stochastic version is robust to mismatch errors in SNR and noise spectrum.

Christopher J. Rozell – 2nd expert on this subject based on the ideXlab platform

  • Cochlear implant speech intelligibility outcomes with structured and unstructured Binary Mask errors
    Journal of the Acoustical Society of America, 2016
    Co-Authors: Abigail A. Kressner, Adam Westermann, Jörg M. Buchholz, Christopher J. Rozell

    Abstract:

    It has been shown that intelligibility can be improved for cochlear implant (CI) recipients with the ideal Binary Mask (IBM). In realistic scenarios where prior information is unavailable, however, the IBM must be estimated, and these estimations will inevitably contain errors. Although the effects of both unstructured and structured Binary Mask errors have been investigated with normal-hearing (NH) listeners, they have not been investigated with CI recipients. This study assesses these effects with CI recipients using Masks that have been generated systematically with a statistical model. The results demonstrate that clustering of Mask errors substantially decreases the tolerance of errors, that incorrectly removing target-dominated regions can be as detrimental to intelligibility as incorrectly adding interferer-dominated regions, and that the individual tolerances of the different types of errors can change when both are present. These trends follow those of NH listeners. However, analysis with a mixed…

  • cochlear implant speech intelligibility outcomes with structured and unstructured Binary Mask errors
    Journal of the Acoustical Society of America, 2016
    Co-Authors: Abigail A. Kressner, Adam Westermann, Jörg M. Buchholz, Christopher J. Rozell

    Abstract:

    It has been shown that intelligibility can be improved for cochlear implant (CI) recipients with the ideal Binary Mask (IBM). In realistic scenarios where prior information is unavailable, however, the IBM must be estimated, and these estimations will inevitably contain errors. Although the effects of both unstructured and structured Binary Mask errors have been investigated with normal-hearing (NH) listeners, they have not been investigated with CI recipients. This study assesses these effects with CI recipients using Masks that have been generated systematically with a statistical model. The results demonstrate that clustering of Mask errors substantially decreases the tolerance of errors, that incorrectly removing target-dominated regions can be as detrimental to intelligibility as incorrectly adding interferer-dominated regions, and that the individual tolerances of the different types of errors can change when both are present. These trends follow those of NH listeners. However, analysis with a mixed effects model suggests that CI recipients tend to be less tolerant than NH listeners to Mask errors in most conditions, at least with respect to the testing methods in each of the studies. This study clearly demonstrates that structure influences the tolerance of errors and therefore should be considered when analyzing BinaryMasking algorithms.

  • A novel Binary Mask estimator based on sparse approximation
    2013 IEEE International Conference on Acoustics Speech and Signal Processing, 2013
    Co-Authors: Abigail A. Kressner, David V. Anderson, Christopher J. Rozell

    Abstract:

    While most single-channel noise reduction algorithms fail to improve speech intelligibility, the ideal Binary Mask (IBM) has demonstrated substantial intelligibility improvements. However, this approach exploits oracle knowledge. The main objective of this paper is to introduce a novel Binary Mask estimator based on a simple sparse approximation algorithm. Our approach does not require oracle knowledge and instead uses knowledge of speech structure.

Philipos C Loizou – 3rd expert on this subject based on the ideXlab platform

  • INTERSPEECH – A new Binary Mask based on noise constraints for improved speech intelligibility.
    , 2020
    Co-Authors: Philipos C Loizou

    Abstract:

    It has been shown that large gains in speech intelligibility can be obtained by using the Binary Mask approach which retains the time-frequency (T-F) units of the mixture signal that are stronger than the interfering noise (Masker) (i.e., SNR>0 dB), and removes the T-F units where the interfering noise dominates. In this paper, we introduce a new Binary Mask for improving speech intelligibility based on noise distortion constraints. A Binary Mask is designed to retain noise overestimated T-F units while discarding noise underestimated T-F units. Listening tests were conducted to evaluate the new Binary Mask in terms of intelligibility. Results from the listening tests indicated that large gains in intelligibility can be achieved by the application of the proposed Binary Mask to noise-corrupted speech even at extremely low SNR levels (-10 dB). Index Terms: speech intelligibility, noise estimation, speech enhancement

  • INTERSPEECH – Binary Mask Estimation for Improved Speech Intelligibility in Reverberant Environments.
    , 2020
    Co-Authors: Oldooz Hazrati, Philipos C Loizou

    Abstract:

    A blind (non-ideal) time-frequency (T-F) Masking technique is proposed for suppressing reverberation. A Binary Mask is estimated at each T-F unit by extracting a single variance-based feature from the reverberant signal and comparing its value against an adaptive threshold. The performance of the estimated Binary Mask is evaluated using intelligibility listening tests with hearing impaired listeners in four moderate to highly reverberant conditions. Results indicated that the proposed T-F Masking technique yielded significant improvements in intelligibility even in highly reverberant conditions (T60 = 1.0 s). This improvement was attributed to the recovery of the vowel/consonant boundaries which are severely smeared in reverberation.

  • Binary Mask estimation for improved speech intelligibility in reverberant environments
    Conference of the International Speech Communication Association, 2012
    Co-Authors: Oldooz Hazrati, Philipos C Loizou

    Abstract:

    A blind (non-ideal) time-frequency (T-F) Masking technique is proposed for suppressing reverberation. A Binary Mask is estimated at each T-F unit by extracting a single variance-based feature from the reverberant signal and comparing its value against an adaptive threshold. The performance of the estimated Binary Mask is evaluated using intelligibility listening tests with hearing impaired listeners in four moderate to highly reverberant conditions. Results indicated that the proposed T-F Masking technique yielded significant improvements in intelligibility even in highly reverberant conditions (T60 = 1.0 s). This improvement was attributed to the recovery of the vowel/consonant boundaries which are severely smeared in reverberation.