Michelle Brachman, Zahra Ashktorab, et al.
PACM HCI
We describe a Monte Carlo method formodel-space noise adaptation of Gaussian mixture models (GMMs). This method combines a single-Gaussian noise model with the GMM speech model to produce an adapted model. It is similar to Parallel Model Combination or model-space Joint, except that it applies to spliced and projected MFCC features rather than to MFCC plus dynamic features. We demonstrate the necessity of re-estimating the noise using both the silence and speech frames rather than just estimating it from silence frames, and obtain improvements on a matched test set without added noise using a system that includes all standard adaptation techniques. Copyright © 2008 ISCA.
Michelle Brachman, Zahra Ashktorab, et al.
PACM HCI
Upendra Chaudhari, Hong-Kwang Jeff Kuo, et al.
INTERSPEECH 2008
Gang Wang, Fei Wang, et al.
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Atsuyoshi Nakamura, Naoki Abe
Electronic Commerce Research