Paper: Improving the precision of automatically constructed human-oriented translation dictionaries

ACL ID W14-1010
Title Improving the precision of automatically constructed human-oriented translation dictionaries
Venue Workshop on Hybrid Approaches to Translation
Session
Year 2014
Authors

In this paper we address the problem of automatic acquisition of a human-oriented translation dictionary from a large-scale parallel corpus. The initial translation equivalents can be extracted with the help of the techniques and tools developed for the phrase-table construction in statistical machine translation. The acquired transla- tion equivalents usually provide good lexi- con coverage, but they also contain a large amount of noise. We propose a super- vised learning algorithm for the detection of noisy translations, which takes into ac- count the context and syntax features, av- eraged over the sentences in which a given phrase pair occurred. Across nine Euro- pean language pairs the number of seri- ous translation errors is reduced by 43.2%, compared to a baseline which uses only p...