Itzulpengintza Automatikoa

Leveraging SNOMED CT terms and relations for machine translation of clinical texts from Basque to Spanish

We present a method for machine translation of clinical texts without using bilingual clinical texts, leveraging the rich terminology and structure of the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT), which is considered the most comprehensive, multilingual clinical health care terminology collection in the world. We evaluate our method for Basque to Spanish translation, comparing the performance with and without using clinical domain resources.

Neural Machine Translation of clinical texts between long distance languages


Objective: To analyze techniques for machine translation of electronic health records (EHRs) between long distance languages, using Basque and Spanish as a reference. We studied distinct configurations of neural machine translation systems and used different methods to overcome the lack of a bilingual corpus of clinical texts or health records in Basque and Spanish.

Adapting NMT to caption translation in Wikimedia Commons for low-resource languages

This paper presents a successful domain adaptation of a general neural machine
translation (NMT) system using a bilingual corpus created with captions for images in Wiki-
media Commons for the Spanish-Basque and English-Irish pairs.
Keywords: Machine Translation, Low-resource languages, Bilingual corpora, Language
resources from Wikipedia


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