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- W1529121676 abstract "Constraint selection for topic-based MDI adaptation of language models This paper presents an unsupervised topic-based language model adaptation method which specializes the standard minimum information discrimination approach by identifying and combining topic-specific features. By acquiring a topic terminology from a thematically coherent corpus, language model adaptation is restrained to the sole probability re-estimation of n-grams ending with some topic-specific words, keeping other probabilities untouched. Experiments are carried out on a large set of spoken documents about various topics. Results show significant perplexity and recognition improvements which outperform results of classical adaptation techniques." @default.
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- W1529121676 date "2009-09-06" @default.
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- W1529121676 title "Constraint selection for topic-based MDI adaptation of language models" @default.
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- W1529121676 doi "https://doi.org/10.21437/interspeech.2009-117" @default.
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