Feature Compensation with Model-Based Estimation for Noise Masking

Young Joon KIM  Nam Soo KIM  

IEICE TRANSACTIONS on Information and Systems   Vol.E90-D   No.2   pp.603-605
Publication Date: 2007/02/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e90-d.2.603
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
speech recognition,  feature compensation,  IMM,  noise masking,  

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In this letter, we propose a new approach to estimate the degree of noise masking based on a sophisticated model for clean speech distribution. This measure, named as noise masking probability (NMP), is incorporated into the feature compensation technique to achieve robust speech recognition in noisy environments. Experimental results show that the proposed approach improves the performance of the baseline recognition system in the presence of various background noises.