Extraction of domain-specific bilingual lexicon from comparable corpora: compositional translation and ranking
This work addresses the challenge of bilingual lexicon extraction for domain-specific terms, which is incremental as it builds on existing methods with a focus on morphological composition.
The paper tackles the problem of extracting translations for morphologically constructed terms from comparable corpora by using compositional translation and ranking methods, achieving an average precision of 91% on the Top1 candidate translation across English-French and English-German language pairs.
This paper proposes a method for extracting translations of morphologically constructed terms from comparable corpora. The method is based on compositional translation and exploits translation equivalences at the morpheme-level, which allows for the generation of "fertile" translations (translation pairs in which the target term has more words than the source term). Ranking methods relying on corpus-based and translation-based features are used to select the best candidate translation. We obtain an average precision of 91% on the Top1 candidate translation. The method was tested on two language pairs (English-French and English-German) and with a small specialized comparable corpora (400k words per language).