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

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$70,000.00
Award Year:
2007
Program:
STTR
Phase:
Phase I
Contract:
N00014-07-M-0349
Award Id:
83488
Agency Tracking Number:
N074-039-0242
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
13619 Valley Oak Circle, ROCKVILLE, MD, 20850
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
620282256
Principal Investigator:
Chiman Kwan
Chief Technology Officer
(240) 505-2641
chiman.kwan@signalpro.net
Business Contact:
Chihwa Yung
President
(301) 315-2322
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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