Ma, N. orcid.org/0000-0002-4112-3109 and Brown, G.J. orcid.org/0000-0001-8565-5476 (2016) Speech localisation in a multitalker mixture by humans and machines. In: Proceedings of INTERSPEECH 2016. INTERSPEECH 2016, 08-12 Sep 2016, San Francisco, USA. ISCA , pp. 3359-3363.
Abstract
Speech localisation in multitalker mixtures is affected by the listener’s expectations about the spatial arrangement of the sound sources. This effect was investigated via experiments with human listeners and a machine system, in which the task was to localise a female-voice target among four spatially distributed male-voice maskers. Two configurations were used: either the masker locations were fixed or the locations varied from trial-to-trial. The machine system uses deep neural networks (DNNs) to learn the relationship between binaural cues and source azimuth, and exploits top-down knowledge about the spectral characteristics of the target source. Performance was examined in both anechoic and reverberant conditions. Our experiments show that the machine system outperformed listeners in some conditions. Both the machine and listeners were able to make use of a priori knowledge about the spatial configuration of the sources, but the effect for headphone listening was smaller than that previously reported for listening in a real room.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 ISCA. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - FP6/FP7 TWO!EARS - 618075 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 12 Feb 2019 13:16 |
Last Modified: | 14 Feb 2019 00:31 |
Published Version: | https://doi.org/10.21437/Interspeech.2016-1149 |
Status: | Published |
Publisher: | ISCA |
Refereed: | Yes |
Identification Number: | 10.21437/Interspeech.2016-1149 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:142466 |