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A Novel Speech Separation Approach for Enhanced Speaker Identification and…

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
83488
Program Year/Program:
2008 / STTR
Agency Tracking Number:
N074-039-0242
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
SIGNAL PROCESSING, INC.
9700 Great Seneca Highway Rockville, MD -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2008
Title: A Novel Speech Separation Approach for Enhanced Speaker Identification and Speech Recognition
Agency / Branch: DOD / NAVY
Contract: N00014-08-C-0677
Award Amount: $500,000.00
 

Abstract:

In order to improve the performance of speaker identification, voiceprint matching, and speech recognition in noisy and clutter (multiple-speaker cocktail party) environment, we need an integrated approach. In this project, we propose a novel approach that addresses this challenging problem in a unified framework. First, we propose to apply microphone(s) to acquire speech signals. Single microphone is more challenging in dealing with noisy conditions. With multiple microphones, it is possible to have much better Direction of Arrivals (DOA) estimation and background noise suppression. As a result, the collected speech will have high SNR. Second, we propose state-of-the-art speech separation techniques to separate voices for both single microphone and multiple microphones. Third, we propose to apply the latest speech enhancement algorithms, including Minimum Mean Square Error (MMSE), Modified Phase Opponency (MPO), and possibly other methods, to remove any residual noise in the separated voice streams. Fourth, robust features based on Mel-frequency Cepstral Coefficients (MFCC) will be applied to extract speech features. Finally, Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) will be used to identify the speaker and recognize the speech. Dynamic Time Warping (DTW) technique will be used for voiceprint verification.

Principal Investigator:

Chiman Kwan
Chief Technology Officer
2405052641
chiman.kwan@signalpro.net

Business Contact:

Chihwa Yung
President
3013152322
chihwa.yung@signalpro.net
Small Business Information at Submission:

SIGNAL PROCESSING, INC.
13619 Valley Oak Circle ROCKVILLE, MD 20850

EIN/Tax ID: 134320631
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
U. MARYLAND
Department of Electrical & Com
2405 A.V. Williams Bldg.
College Park, MD 20742
Contact: Carol Espy-Wilson
Contact Phone: (301) 405-7411
RI Type: Nonprofit college or university