期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2012
卷号：2012
出版社：ACL Anthology
摘要：We propose an approach that biases machine
translation systems toward relevant translations
based on topic-specific contexts, where
topics are induced in an unsupervised way
using topic models; this can be thought of
as inducing subcorpora for adaptation without
any human annotation. We use these topic
distributions to compute topic-dependent lexical
weighting probabilities and directly incorporate
them into our translation model as
features. Conditioning lexical probabilities
on the topic biases translations toward topicrelevant
output, resulting in significant improvements
of up to 1 BLEU and 3 TER on
Chinese to English translation over a strong
baseline.
