Discriminative training of language models for text and...

Details Discriminative training of language models for text and... Discriminative training of language models for text and...

2008-05-27

2008-05-27

Dorvil, Richemond (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

C704S009000, C704S240000

Reexamination Certificate

active

10453349

ABSTRACT:
Methods are disclosed for estimating language models such that the conditional likelihood of a class given a word string, which is very well correlated with classification accuracy, is maximized. The methods comprise tuning statistical language model parameters jointly for all classes such that a classifier discriminates between the correct class and the incorrect ones for a given training sentence or utterance. Specific embodiments of the present invention pertain to implementation of the rational function growth transform in the context of a discriminative training technique for n-gram classifiers.

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Chelba, C.; and Acero, A.; “Discriminative Training of N-gram Classifiers for Speech and Text Routing,” Microsoft Research, Sep. 2003, pp. 1-4.
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