BVS Corpus: A Multilingual Parallel Corpus of Biomedical Scientific Texts
This provides a valuable resource for researchers in biomedical natural language processing, enabling improved machine translation for scientific texts, though it is incremental as it applies existing methods to new data.
The authors tackled the lack of multilingual parallel corpora for biomedical texts by developing the BVS Corpus from the Health Virtual Library, automatically aligning sentences in English, Spanish, and Portuguese, and training neural machine translation systems that outperformed related works on scientific biomedical articles.
The BVS database (Health Virtual Library) is a centralized source of biomedical information for Latin America and Carib, created in 1998 and coordinated by BIREME (Biblioteca Regional de Medicina) in agreement with the Pan American Health Organization (OPAS). Abstracts are available in English, Spanish, and Portuguese, with a subset in more than one language, thus being a possible source of parallel corpora. In this article, we present the development of parallel corpora from BVS in three languages: English, Portuguese, and Spanish. Sentences were automatically aligned using the Hunalign algorithm for EN/ES and EN/PT language pairs, and for a subset of trilingual articles also. We demonstrate the capabilities of our corpus by training a Neural Machine Translation (OpenNMT) system for each language pair, which outperformed related works on scientific biomedical articles. Sentence alignment was also manually evaluated, presenting an average 96% of correctly aligned sentences across all languages. Our parallel corpus is freely available, with complementary information regarding article metadata.