Introducing copa-trad version 2.0 a parallel corpus-based system for translation research, teaching and practice
DOI:
https://doi.org/10.5007/2175-8026.2020v73n1p297Abstract
This paper describes COPA-TRAD Version 2.0, a parallel corpus-based system developed at the Universidade Federal de Santa Catarina (UFSC) for translation research, teaching and practice. COPA-TRAD enables the user to investigate the practices of professional translators by identifying translational patterns related to a particular element or linguistic pattern. In addition, the system allows for the comparison between human translation and automatic translation provided by three well-known machine translation systems available on the Internet (Google Translate, Microsoft Translator and Yandex). Currently, COPA-TRAD incorporates five subcorpora (Children's Literature, Literary Texts, Meta-Discourse in Translation, Subtitles and Legal Texts) and provides the following tools: parallel concordancer, monolingual concordancer, wordlist and a DIY Tool that enables the user to create his own parallel disposable corpus. The system also provides a POS-tagging tool interface to analyze and classify the parts of speech of a text.
References
BAKER, M. Corpora in Translation Studies. An Overview and Suggestions for Future Research. Target, 7(2). pp. 223-243, 1995.
FERNANDES, L. P. A Portal into the Unknown: Designing, Building, and Processing a Parallel Corpus. CTIS Occasional Papers, Vol. 4, pp. 16-36, 2009.
FERNANDES, L. P. On the use of a Portuguese-English parallel corpus of children’s fantasy literature in translator education. Cadernos de Tradução, Vol. 2, No. 20, pp. 141-163, 2007.
FERNANDES, L. P. Practices of Translating Names in Children’s Fantasy Literature: A Corpus-based Study. Florianópolis, 2004. (Doutorado em Inglês e Linguística Aplicada) – Curso de Pós-Graduação em Inglês, Universidade Federal de Santa Catarina.
OLOHAN, M. Introducing Corpora in Translation Studies. Londres: Routledge, 2004.
SCOTT, M. Mapping key words to problem and solution. Patterns of Text: in Honour of Michael Hoey, Amsterdam. Benjamins. p. 109-127, 2001.
SILVA, C. E. Developing Online Parallel Corpus-based Processing Tools for Translation Research and Pedagogy. Florianópolis, 2013. Dissertação (Mestrado em Inglês e Linguística Aplicada) - Curso de Pós-Graduação em Inglês, Universidade Federal de Santa Catarina.
SILVA, C. E. Utilização de Técnicas de Mineração de Textos em Corpora Paralelo para Auxílio na Pesquisa Acadêmica em Estudos da Tradução: Um Estudo de Caso. 64 f. Trabalho de Conclusão de Curso (Especialização) – Curso de Pós-Graduação em Engenharia e Projetos de Software, Universidade do Sul de Santa Catarina, Florianópolis, 2014.
SILVA, C. E. Corpus Mining: A New Perspective on Translation Studies. Florianópolis, 2018. (Estudos da Linguagem) – Programa de Pós-Graduação em Inglês, Universidade Federal de Santa Catarina.
SINCLAIR, J. M. Corpus, Concordance, Collocation. Oxford: Oxford University Press, 1991.
VARGA, D., L. NÉMETH, P., HALÁCSY, A., KORNAI, V., TRÓN, V., NAGY. Parallel corpora for medium density languages. Proceedings of the RANLP 2005, p. 590-596, 2005.
ZIPF, G. K. Human Behaviour and the Principle of Least Effort. Cambridge: Addison-Wesley Press, 1949.
IMAO, Y. Javascript-based online concordancer, 2008. Disponível em: <http://www.ne.jp/asahi/yasu/casualconc/casualconcpages/pconc.html>. Acesso em: 9 fev. 2017.
WU, Y., SCHUSTER, M., CHEN, Z., LE, Q. V., NOROUZI, M., MACHEREY, W., & KLINGNER, J. Google’s neural machine translation system: Bridging the gap between human and machine translation , (p. 1-23). arXiv preprint arXiv:1609.08144.
