Summary of the paper
| Title | Automatic Translation of Biomedical Terms by Supervised Machine Learning |
|---|---|
| Authors | Vincent Claveau |
| Abstract | In this paper, we present a simple yet efficient automatic system to translate biomedical terms. It mainly relies on a machine learning approach able to infer rewriting rules from pair of terms in two languages. Given a new term, these rules are then used to transform the initial term into its translation. Since conflicting rules may produce different translations, we also use language modeling to single out the best candidate. We report experiments on different language pairs (including Czech, English, French, Italian, German, Portuguese, Spanish and even Russian); our approach yields good results (varying according to the considered languages) and outperforms existing ones for the French-English pair. |
| Language | Multiple languages |
| Topics | Acquisition, Machine Learning, Machine Translation, SpeechToSpeech Translation, Multilinguality |
Full paper |
Automatic Translation of Biomedical Terms by Supervised Machine Learning |
Slides |
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| Bibtex | @InProceedings{CLAVEAU08.173, author = {Vincent Claveau}, title = {Automatic Translation of Biomedical Terms by Supervised Machine Learning}, booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)}, year = {2008}, month = {may}, date = {28-30}, address = {Marrakech, Morocco}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-4-0}, note = {http://www.lrec-conf.org/proceedings/lrec2008/}, language = {english} } |