AALF: Adjustable Adaptive Language speech Filter

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-07-C-0105
Agency Tracking Number: F071-079-0408
Amount: $99,985.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solitcitation Year: 2007
Solitcitation Topic Code: AF071-079
Solitcitation Number: 2007.1
Small Business Information
21ST CENTURY TECHNOLOGIES, INC.
4515 Seton Center Parkway, Suite 320, Austin, TX, 78759
Duns: 158034665
Hubzone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Matthew McClain
 Sr. Research Engineer
 (512) 342-0010
 mmcclain@21technologies.com
Business Contact
 Irene Williams
Title: Chief Operations Officer
Phone: (512) 342-0010
Email: SBIR_Admin@21technologies.com
Research Institution
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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