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Contribution to terminology internationalization by word alignment in parallel corpora
Louise Deléger1, Magnus Merkel, Pierre Zweigenbaum
1INSERM, U729, Paris, F-75006, France.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 24, 2007
Summary
Natural language processing word alignment can help medical translators by automatically extracting thousands of new English-to-French term translations from large text corpora, reducing manual effort.
Area of Science:
- Computational linguistics
- Medical informatics
- Natural Language Processing
Background:
- Medical vocabulary translation is time-consuming and requires specialized expertise.
- Automated methods are needed to improve translation efficiency.
Purpose of the Study:
- To evaluate the effectiveness of word alignment in parallel corpora for alleviating the task of medical vocabulary translation.
- To assess the number and quality of French translations generated for English medical terms.
Main Methods:
- Constructed a large English-French parallel corpus.
- Utilized state-of-the-art tools for document, sentence, and word alignment.
- Projected English terms from controlled vocabularies (MeSH, SNOMED CT, MedlinePlus Health Topics) onto aligned word pairs.
Main Results:
- Generated several thousand new French translations for input English terms.
- The number of translations was directly proportional to the size of the input vocabularies.
Conclusions:
- Word alignment methods can efficiently extract new term translations from extensive texts.
- This approach aids human translators by improving vocabulary translation coverage with moderate review effort.
- Future work includes applying methods to larger corpora and refining term extraction techniques.
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