2019/05/06 by Felipe Soares, Soares, Felipe, Viviane P. Moreira +4 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Software Engineering Research #Text Readability and Simplification #cs.CL
paper · pdf · doi:10.48550/arxiv.1905.01852
Published in Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
arxiv created 2019/05/06 · openalex publication_date 2019/05/06 · arxiv updated 2019/05/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.