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14

FSMNLP
2008
Springer

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Learning with Weighted Transducers

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Learning with Weighted Transducers

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Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine translation. This paper shows how weighted transducers can be combined with existing learning algorithms to form powerful techniques for sequence learning problems. Keywords. Learning, kernels, classification, regression, ranking, clustering, weighted automata, weighted transducers, rational powers series.

Corinna Cortes, Mehryar Mohri

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Added	29 Oct 2010
Updated	29 Oct 2010
Type	Conference
Year	2008
Where	FSMNLP
Authors	Corinna Cortes, Mehryar Mohri

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