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Background Adaptation for Improved Listening Experience in Broadcasting

Liu, Qingju, Wang, Wenwu, Fazenda, Bruno M, Cox, Trevor J and Tang, Yan (2019) Background Adaptation for Improved Listening Experience in Broadcasting In: International Conference on Acoustics, Speech, and Signal Processing : Signal Processing: Empowering Science and Technology for Humankind, 12 - 17 May 2019, Brighton, UK.

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Abstract

The intelligibility of speech in noise can be improved by modifying the speech. But with object-based audio, there is the possibility of altering the background sound while leaving the speech unaltered. This may prove a less intrusive approach, affording good speech intelligibility without overly compromising the perceived sound quality. In this study, the technique of spectral weighting was applied to the background. The frequency-dependent weightings for adaptation were learnt by maximising a weighted combination of two perceptual objective metrics for speech intelligibility and audio quality. The balance between the two objective metrics was determined by the perceptual relationship between intelligibility and quality. A neural network was trained to provide a fast solution for real-time processing. Tested in a variety of background sounds and speech-to-background ratios (SBRs), the proposed method led to a large intelligibility gain over the unprocessed baseline. Compared to an approach using constant weightings, the proposed method was able to dynamically preserve the overall audio quality better with respect to SBR changes.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
NameEmailORCID
Liu, Qingjuq.liu@surrey.ac.uk
Wang, WenwuW.Wang@surrey.ac.uk
Fazenda, Bruno M
Cox, Trevor J
Tang, Yan
Date : 17 April 2019
DOI : 10.1109/ICASSP.2019.8682687
Copyright Disclaimer : Copyright 2019 IEEE. Published in the IEEE 2019 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), scheduled for 12-17 May, 2019, in Brighton, United Kingdom. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 908-562-3966.
Uncontrolled Keywords : Background adaptation, intelligibility, audio quality, listening experience, neural network
Depositing User : Charlene King
Date Deposited : 05 Mar 2019 10:30
Last Modified : 24 May 2019 10:12
URI: http://epubs.surrey.ac.uk/id/eprint/850667

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