BVS Corpus: A Multilingual Parallel Corpus of Biomedical Scientific Texts

TL;DR

This paper introduces BVS Corpus, a multilingual biomedical parallel corpus in English, Spanish, and Portuguese, created from the BVS database, and demonstrates its effectiveness for training neural machine translation systems.

Contribution

The paper presents a new multilingual biomedical parallel corpus derived from BVS and shows its utility in improving neural machine translation performance.

Findings

Achieved 96% correct sentence alignment accuracy.

Trained NMT systems that outperform existing models on biomedical texts.

Corpus is freely available with article metadata.

Abstract

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.