Back-translation approach for code-switching machine translation: A case study
Masoud, Maraim Torregrosa, Daniel Buitelaar, Paul Arčan, Mihael
Masoud, Maraim
Torregrosa, Daniel
Buitelaar, Paul
Arčan, Mihael
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Publication Date
2019-12-05
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Conference Paper
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Masoud, Maraim, Torregrosa, Daniel, Buitelaar, Paul, & Arčan, Mihael. (2019). Back-translation approach for code-switching machine translation: A case study. Paper presented at the 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, Galway, Ireland, 05-06 December.
Abstract
Recently, machine translation has demonstrated significant progress in terms of translation quality. However, most of the research has focused on translating with pure monolingual texts in the source and the target side of the parallel corpora, when in fact code-switching is very common in communication nowadays. Despite the importance of handling code-switching in the translation task, existing machine translation systems fail to accommodate the code-switching content. In this paper, we examine the phenomenon of code-switching in machine translation for low-resource languages. Through different approaches, we evaluate the performance of our systems and make some observations about the role of code-mixing in the available corpora.
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AICS2019
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Attribution-NonCommercial-NoDerivs 3.0 Ireland