AALF: Adjustable Adaptive Language speech Filter

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,985.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
FA8750-07-C-0105
Award Id:
81975
Agency Tracking Number:
F071-079-0408
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
4515 Seton Center Parkway, Suite 320, Austin, TX, 78759
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
158034665
Principal Investigator:
MatthewMcClain
Sr. Research Engineer
(512) 342-0010
mmcclain@21technologies.com
Business Contact:
IreneWilliams
Chief Operations Officer
(512) 342-0010
SBIR_Admin@21technologies.com
Research Institute:
n/a
Abstract
The ability to efficiently process intelligence data is critical to fighting the global war on terror. A major source of this data is recorded speech. Therefore, the performance of speech processing applications (speech recognition and speaker identification applications, for example) depends on pre-processing to find the regions in the recording where speech is present. Although current methods have had success isolating human speech from interfering background noise, these methods have not addressed non-language speech sounds (NLSS), i.e., sighs, coughing, and backchannel sounds ("un-huh", "hmm", etc.). 21st Century Technologies (21CT) proposes Adjustable Adaptive Language speech Filter (AALF) as a robust NLSS filtering system that combines a signal processing feature extraction component, an adaptive machine learning mechanism that provides robustness to various input conditions, and a post-processing component that includes a user-specified detection threshold to tune AALF's performance for specific speech processing applications that follow. AALF will improve the generation of actionable intelligence by decreasing the cost of creating speech training databases and improving the performance of speech processing applications.

* information listed above is at the time of submission.

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