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A non-intrusive method for estimating binaural speech intelligibility from noise-corrupted signals captured by a pair of microphones

Tang, Yan, Liu, Qingju, Wang, Wenwu and Cox, Trevor J. (2017) A non-intrusive method for estimating binaural speech intelligibility from noise-corrupted signals captured by a pair of microphones Speech Communication, 96. pp. 116-128.

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Abstract

A non-intrusive method is introduced to predict binaural speech intelligibility in noise directly from signals captured using a pair of microphones. The approach combines signal processing techniques in blind source separation and localisation, with an intrusive objective intelligibility measure (OIM). Therefore, unlike classic intrusive OIMs, this method does not require a clean reference speech signal and knowing the location of the sources to operate. The proposed approach is able to estimate intelligibility in stationary and fluctuating noises, when the noise masker is presented as a point or diffused source, and is spatially separated from the target speech source on a horizontal plane. The performance of the proposed method was evaluated in two rooms. When predicting subjective intelligibility measured as word recognition rate, this method showed reasonable predictive accuracy with correlation coefficients above 0.82, which is comparable to that of a reference intrusive OIM in most of the conditions. The proposed approach offers a solution for fast binaural intelligibility prediction, and therefore has practical potential to be deployed in situations where on-site speech intelligibility is a concern.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Tang, Yan
Liu, Qingjuq.liu@surrey.ac.uk
Wang, WenwuW.Wang@surrey.ac.uk
Cox, Trevor J.
Date : 13 December 2017
Funders : Engineering and Physical Sciences Research Council (EPSRC)
Identification Number : 10.1016/j.specom.2017.12.005
Copyright Disclaimer : © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).
Uncontrolled Keywords : Objective intelligibility measure; Non-intrusive; Binaural intelligibility; Noise; Glimpsing; Neural network; Blind source separation; Blind source localisation; Microphone
Depositing User : Clive Harris
Date Deposited : 19 Dec 2017 08:18
Last Modified : 14 Mar 2018 16:03
URI: http://epubs.surrey.ac.uk/id/eprint/845438

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