An Auditory Scene Analysis Approach to Speech Segregation

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$749,947.00
Award Year:
2012
Program:
STTR
Phase:
Phase II
Contract:
FA9550-12-C-0018
Award Id:
n/a
Agency Tracking Number:
F09B-T12-0211
Solicitation Year:
2009
Solicitation Topic Code:
AF09-BT12
Solicitation Number:
2009.B
Small Business Information
Shannon Campbell, 15127 NE 198TH ST, Woodinville, WA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
112141663
Principal Investigator:
DeLiangWang
Professor
(614) 292-6827
dwang@cse.ohio-state.edu
Business Contact:
ShannonCampbell
President
(425) 402-1808
kuzershan@yahoo.com
Research Institute:
The Ohio State University
DeLiang Wang
Dept. of Computer Sci.&Eng.
2015 Neil Ave.
Columbus, OH, 43210-1277
(614) 292-6827

Abstract
ABSTRACT: This Phase II proposal seeks to develop a prototype speech segregation system that can significantly improve intelligibility of noisy speech for human listeners, a technical challenge that has eluded a solution for decades. Motivated by principles of auditory perception, system development is based on an auditory scene analysis approach to speech segregation. This approach differs substantially from traditional speech enhancement techniques, and its promise has been successfully demonstrated in Phase I research. The proposed effort will address both simultaneous organization and sequential organization in computational auditory scene analysis, as well as efficient implementation. The prototype system will be systematically evaluated using a set of clear performance milestones involving normal-hearing and hearing-impaired listeners and a variety of speech and background interference. BENEFIT: Speech segregation technology that can improve speech intelligibility in noisy environments for human listeners has huge potential for commercialization. Practical applications include hearing aid design and cochlear implants where noise reduction is a major unsolved problem, better consumer devices for speech communication in adverse acoustic conditions, and robust automatic speech and speaker recognition. These applications occur in both civilian and military domains.

* information listed above is at the time of submission.

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