Translating medical terminologies through word alignment in parallel text corpora

Authors:
Louise Delé/ger;Magnus Merkel;Pierre Zweigenbaum
Affiliations:
INSERM, UMR_S 872, Eq. 20, Centre des cordeliers, Paris F-75006, France and Université/ Pierre et Marie Curie, Paris F-75006, France/ Université/ Paris-Descartes, Paris F-75006, France;Department of Computer and Information Science, Linkö/ping University, Sweden;CNRS UPR3251, LIMSI, Orsay F-91403, France
Venue:
Journal of Biomedical Informatics
Year:
2009

Citing 9
Cited 1

Foundations of statistical natural language processing

Foundations of statistical natural language processing
Bilingual Sentence Alignment: Balancing Robustness and Accuracy

Machine Translation
The Web as a parallel corpus

Computational Linguistics - Special issue on web as corpus
A program for aligning sentences in bilingual corpora

Computational Linguistics - Special issue on using large corpora: I
The mathematics of statistical machine translation: parameter estimation

Computational Linguistics - Special issue on using large corpora: II
Flow network models for word alignment and terminology extraction from bilingual corpora

COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
K-vec: a new approach for aligning parallel texts

COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Automatic processing of multilingual medical terminology: applications to thesaurus enrichment and cross-language information retrieval

Artificial Intelligence in Medicine
Translating biomedical terms by inferring transducers

AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine

Letter to the Editor: Translation and localization of SNOMED CT in China: A pilot study

Artificial Intelligence in Medicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

Developing international multilingual terminologies is a time-consuming process. We present a methodology which aims to ease this process by automatically acquiring new translations of medical terms based on word alignment in parallel text corpora, and test it on English and French. After collecting a parallel, English-French corpus, we detected French translations of English terms from three terminologies-MeSH, SNOMED CT and the MedlinePlus Health Topics. We obtained respectively for each terminology 74.8%, 77.8% and 76.3% of linguistically correct new translations. A sample of the MeSH translations was submitted to expert review and 61.5% were deemed desirable additions to the French MeSH. In conclusion, we successfully obtained good quality new translations, which underlines the suitability of using alignment in text corpora to help translating terminologies. Our method may be applied to different European languages and provides a methodological framework that may be used with different processing tools.