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The Scielo database is an important source of scientific information in LatinAmerica, containing articles from several research domains. A strikingcharacteristic of Scielo is that many of its full-text contents are presentedin more than one language, thus being a potential source of parallel corpora.In this article, we present the development of a parallel corpus from Scielo inthree languages: English, Portuguese, and Spanish. Sentences were automaticallyaligned using the Hunalign algorithm for all language pairs, and for a subsetof trilingual articles also. We demonstrate the capabilities of our corpus bytraining a Statistical Machine Translation system (Moses) for each languagepair, which outperformed related works on scientific articles. Sentencealignment was also manually evaluated, presenting an average of 98.8% correctlyaligned sentences across all languages. Our parallel corpus is freely availablein the TMX format, with complementary information regarding article metadata.

A Large Parallel Corpus of Full-Text Scientific Articles