Background adaptation for improved listening experience in broadcasting

Tang, Y, Cox, TJ ORCID:, Fazenda, BM ORCID:, Liu, Q and Wang, W 2019, Background adaptation for improved listening experience in broadcasting , in: 44th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, 12-17 May 2019, Brighton, UK.

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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 (Paper)
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher: IEEE
ISBN: 9781479981311
ISSN: 2379-190X
Related URLs:
Funders: Engineering and Physical Sciences Research Council (EPSRC)
Depositing User: USIR Admin
Date Deposited: 13 May 2019 08:32
Last Modified: 16 Feb 2022 02:03

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