Large and Diverse Language Models for Statistical Machine Translation
Edinburgh Research Explorer (University of Edinburgh)Published 19 November 2009Open access
Holger Schwenk, Philipp Koehn
Citations38
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TL;DR
Methods to combine large language models trained from diverse text sources and applies them to a state-ofart French–English and Arabic–English machine translation system are presented.
Abstract
This paper presents methods to combine large language models trained from diverse text sources and applies them to a stateof-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. 1
Keywords
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