A Novel Speech Separation Approach for Enhanced Speaker Identification and Speech Recognition

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-07-M-0349
Agency Tracking Number: N074-039-0242
Amount: $70,000.00
Phase: Phase I
Program: STTR
Awards Year: 2007
Solitcitation Year: 2007
Solitcitation Topic Code: N07-T039
Solitcitation Number: N/A
Small Business Information
SIGNAL PROCESSING, INC.
13619 Valley Oak Circle, ROCKVILLE, MD, 20850
Duns: 620282256
Hubzone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: Y
Principal Investigator
 Chiman Kwan
 Chief Technology Officer
 (240) 505-2641
 chiman.kwan@signalpro.net
Business Contact
 Chihwa Yung
Title: President
Phone: (301) 315-2322
Email: chihwa.yung@signalpro.net
Research Institution
 UNIV. OF MARYLAND
 Carol Espy-Wilson
 Department of Electrical and
Computer Engineering
College Park, MD, 20742
 (301) 405-7411
 Nonprofit college or university
Abstract
In order to improve the performance of speaker identification and speech recognition, we need an integrated approach. We propose a novel approach that addresses all of the above challenges in a unified framework. First, we propose to apply microphone arrays (1-D, 2-D or 3-D) to acquire speech signals. The arrays can provide better Direction of Arrivals (DOA) estimation and improves background noise suppression. The collected speech will have high SNR. Second, we propose to apply the latest speech enhancement algorithm developed by our subcontractor at UM. The idea is based on Modified Phase Opponency (MPO) and does not require noise estimation. Third, for each separated speech stream, there may still be regions that have poor SNR. So we propose to apply spectrogram reconstruction algorithm to repair the poor SNR regions. Fourth, robust features based on Mel-frequency Cepstral Coefficients (MFCC) will be applied to the repaired spectrogram. Finally, Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) will be used to identify the speaker and recognize the speech.

* information listed above is at the time of submission.

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