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A NEW MASK-BASED OBJECTIVE MEASURE FOR PREDICTING THE INTELLIGIBILITY OF BINARY MASKED SPEECH.

作者信息

Yu Chengzhu, Wójcicki Kamil K, Loizou P C, Hansen John H L

机构信息

Dept. of Electrical Engineering, Erik Jonsson School of Enigneering and Computer Science, University of Texas at Dallas, Richardson, TX 75080.

出版信息

Proc IEEE Int Conf Acoust Speech Signal Process. 2013. doi: 10.1109/ICASSP.2013.6639025.

Abstract

Mask-based objective speech-intelligibility measures have been successfully proposed for evaluating the performance of binary masking algorithms. These objective measures were computed directly by comparing the estimated binary mask against the ground truth ideal binary mask (IdBM). Most of these objective measures, however, assign equal weight to all time-frequency (T-F) units. In this study, we propose to improve the existing mask-based objective measures by weighting each T-F unit according to its target or masker loudness. The proposed objective measure shows significantly better performance than two other existing mask-based objective measures.

摘要

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引用本文的文献

1
Evaluation of the importance of time-frequency contributions to speech intelligibility in noise.
J Acoust Soc Am. 2014 May;135(5):3007-16. doi: 10.1121/1.4869088.

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