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ICASSP
2009
IEEE

The effectiveness of histogram equalization on environmental model adaptation

10 years 4 months ago
The effectiveness of histogram equalization on environmental model adaptation
In this paper, we introduce a new histogram equalizationbased environmental model adaptation method for robust speech recognition in noise environments. The proposed method adapts initially-trained acoustic mean models of a speech recognizer into the environmentally matched models. The covariance models are adapted by using utterance-level local covariance matrices. We performed a series of experiments based on the Aurora2 framework to examine the effectiveness of the proposed environmental model adaptation technique. In both clean and multi-condition trainings, the proposed approach achieved substantial performance improvements over the baseline speech recognizers.
Youngjoo Suh, Hoirin Kim
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Youngjoo Suh, Hoirin Kim
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