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Use of a linear projection (LP) function to transform multiple sets of acoustic models into a single set of acoustic models is proposed for characterizing testing environments for robust automatic speech recognition. The LP function is an extension of the linear regression (LR) function used in maximum likelihood linear regression (MLLR) and maximum a posteriori linear regression (MAPLR) by incorporating...
In this paper, we propose an integration process of feature compensation and selection on the collective acoustic feature sets to derive a set of advanced acoustic features for speaker state recognition. For feature normalization, we perform a two-dimensional histogram equalization (2-D HEQ) normalization to reduce variability of speaker and speaking environment factors. For feature selection, we...
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