Comparison of effects on subjective intelligibility and quality of speech in babble for two algorithms: A deep recurrent neural network and spectral subtraction-Reference-Cited by-同舟云学术

Comparison of effects on subjective intelligibility and quality of speech in babble for two algorithms: A deep recurrent neural network and spectral subtraction

Published:2019-03 Issue:3 Volume:145 Page:1493-1503
ISSN:0001-4966
Container-title:The Journal of the Acoustical Society of America
language:en
Short-container-title:The Journal of the Acoustical Society of America

Author:

Keshavarzi Mahmoud¹,Goehring Tobias²,Turner Richard E.³,Moore Brian C. J.¹

Affiliation:

1. Department of Psychology, University of Cambridge, Cambridge, United Kingdom

2. MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom

3. Department of Engineering, University of Cambridge, Cambridge, United Kingdom

Funder

Engineering and Physical Sciences Research Council

Action on Hearing Loss

Allen Trust

Publisher

Acoustical Society of America (ASA)

Subject

Acoustics and Ultrasonics,Arts and Humanities (miscellaneous)

Link

http://asa.scitation.org/doi/pdf/10.1121/1.5094765

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