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This research aims to improve statistical machine translation performance using monolingual data from comparable corpora.

January 1, 2008Open Access

Language and translation model adaptation using comparable corpora

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This research aims to improve statistical machine translation performance using monolingual data from comparable corpora.
Developed a novel method to utilize monolingual target language documents for translation improvement.
Searched a monolingual dataset to find comparable texts for each source document.
Adapted both language and translation models based on comparable documents to enhance translation accuracy.
The adapted translation model showed substantial performance gains compared to the baseline system.
Incorporating comparable documents allowed for better alignment with the intended meaning of source texts.
Overall improvements were observed in the generation of more fluent and contextually relevant translations.

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Randomized trial demonstrates improved translation performance using monolingual comparable corpora, suggesting better resource utilization.

Snover et al. (2008) studied this question.

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Randomized trial demonstrates improved translation performance using monolingual comparable corpora, suggesting better resource utilization.