Accumulating transformations for hierarchical linear...

Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition

Reexamination Certificate

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C704S256200

Reexamination Certificate

active

07089183

ABSTRACT:
A new iterative hierarchical linear regression method for generating a set of linear transforms to adapt HMM speech models to a new environment for improved speech recognition is disclosed. The method determines a new set of linear transforms at an iterative step by Estimate-Maximize (EM) estimation, and then combines the new set of linear transforms with the prior set of linear transforms to form a new merged set of linear transforms. An iterative step may include realignment of adaptation speech data to the adapted HMM models to further improve speech recognition performance.

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Afify,M., Y.Gong, and J.-P.Haton, “A Unified Maximum Likelihood Approach to Acoustic Mismatch Compensation: Application to Noisy Lombard Speech Recognition,” Proc. 1997 IEEE IAcoust., Speech, and Sig. Proc., ICASSP-97,Apr. 21-24, 1997, vol. 2, pp. 839-842.

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