Paper: Collocation Translation Acquisition Using Monolingual Corpora

ACL ID P04-1022
Title Collocation Translation Acquisition Using Monolingual Corpora
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004

Collocation translation is important for machine translation and many other NLP tasks. Unlike previous methods using bilingual parallel corpora, this paper presents a new method for acquiring collocation translations by making use of monolingual corpora and linguistic knowledge. First, dependency triples are extracted from Chinese and English corpora with dependency parsers. Then, a dependency triple translation model is estimated using the EM algorithm based on a dependency correspondence assumption. The generated triple translation model is used to extract collocation translations from two monolingual corpora. Experiments show that our approach outperforms the existing monolingual corpus based methods in dependency triple translation and achieves promising results in collocation translat...