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Finding Terminology Translations From Non-Parallel Corpora

McKeown, Kathleen; Fung, Pascale

In this paper, we present an initial algorithm for translating technical terms using a pair of non-parallel corpora. Evalution results show translation precisions at around 30% when only the top candidate is considered. While this precision is lower than that achieved with parallel corpora, we show that top 20 candidate output from our algorithm allows translators to increase their accuracy by 50.9%. In the following sections, we first describe a pair of non-parallel corpora we use for experiments, and then we introduce the Word Relation Matrix (WoRM), a statistical word feature representation for technical term translation from non-parallel corpora. We evaluate the effectiveness of this feature with two sets of experiments, using English/English, and English/Japanese non-parallel corpora.


More About This Work

Academic Units
Computer Science
Proceedings of 5th International Workshop of Very Large Corpora (WVLC-5)
Published Here
April 29, 2013