Machine translation: a critical look at the performance of rule-based and statistical machine translation

Autores/as

DOI:

https://doi.org/10.5007/2175-7968.2020v40n1p54

Resumen

The essay provides a critical assessment of the performance of two distinct machine translation systems, Systran and Google Translate. First, a brief overview of both rule-based and statistical machine translation systems is provided followed by a discussion concerning the issues involved in the automatic and human evaluation of machine translation outputs. Finally, the German translations of Mark Twain’s The Awful German Language translated by Systran and Google Translate are being critically evaluated highlighting some of the linguistic challenges faced by each translation system.

Biografía del autor/a

Brita Banitz, Universidad de las Américas Puebla, San Andrés Cholula,

PhD (2005) in English (Language and Linguistics) from Purdue University, IN, USA. MA (2002) in Teaching English as a Second Language from Kent State University, OH, USA. BA (2000) in German Linguistics from the Technical University of Dresden, Germany. Associate Professor of Applied Linguistics at the Universidad de las Américas Puebla, Mexico.

Citas

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Schneider, Michael. “Die schreckliche deutsche Sprache.” https://www.hmtm-hannover.de/uploads/media/Die_schreckliche_deutsche_Sprache_06.pdf. Accessed 13 February 2019.

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Somers, Harold L. “Machine translation: History, development, and limitations.” The Oxford handbook of translation studies. Ed. Kirsten Malmkjaer and Kevin Windle. Oxford: Oxford University Press, 2011. 427-440.

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Publicado

2020-01-22

Cómo citar

Banitz, B. (2020). Machine translation: a critical look at the performance of rule-based and statistical machine translation. Cadernos De Tradução, 40(1), 54–71. https://doi.org/10.5007/2175-7968.2020v40n1p54

Número

Vol. 40 Núm. 1 (2020): Edição Regular

Sección

Artículos

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