The Scielo database is an important source of scientific information in Latin America, containing articles from several research domains. A striking characteristic of Scielo is that many of its full-text contents are presented in 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 in three languages: English, Portuguese, and Spanish. Sentences were automatically aligned using the Hunalign algorithm for all language pairs, and for a subset of trilingual articles also. We demonstrate the capabilities of our corpus by training a Statistical Machine Translation system (Moses) for each language pair, which outperformed related works on scientific articles. Sentence alignment was also manually evaluated, presenting an average of 98.8% correctly aligned sentences across all languages. Our parallel corpus is freely available in the TMX format, with complementary information regarding article metadata.

本文提出利用Scielo数据库建立了一个包含英语、葡萄牙语和西班牙语的多语种平行语料库，使用Hunalign算法对句子进行自动对齐，并用Moses对每种语言对进行了翻译，证明该语料库在科学文章中的机器翻译方面表现优异，同时还提供了包含元数据的TMX格式免费使用。

一个大规模的全文科学文章平行语料库