Large and Diverse Language Models for Statistical Machine Translation

Holger Schwenk, Philipp Koehn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents methods to combine large language models trained from diverse text sources and applies them to a state-of-art French–English and Arabic–English machine translation system. We show gains of over 2 BLEU points over a strong baseline by using continuous space language models in re-ranking.
Original languageEnglish
Title of host publicationThird International Joint Conference on Natural Language Processing, IJCNLP 2008, Hyderabad, India, January 7-12, 2008
Pages661-666
Number of pages6
Publication statusPublished - 2008

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