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13

ACL
2010

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Domain Adaptation of Maximum Entropy Language Models

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Domain Adaptation of Maximum Entropy Language Models

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We investigate a recently proposed Bayesian adaptation method for building style-adapted maximum entropy language models for speech recognition, given a large corpus of written language data and a small corpus of speech transcripts. Experiments show that the method consistently outperforms linear interpolation which is typically used in such cases.

Tanel Alumäe, Mikko Kurimo

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ACL 2010 | Bayesian Adaptation Method | Computational Linguistics | Entropy Language Models | Large Corpus |

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Added	10 Feb 2011
Updated	10 Feb 2011
Type	Journal
Year	2010
Where	ACL
Authors	Tanel Alumäe, Mikko Kurimo

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