Back-translation approach for code-switching machine translation: A case study

    Research output: Contribution to a Journal (Peer & Non Peer)Conference articlepeer-review

    1 Citation (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)128-139
    Number of pages12
    JournalCEUR Workshop Proceedings
    Volume2563
    Publication statusPublished - 2019
    Event27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2019 - Galway, Ireland
    Duration: 5 Dec 20196 Dec 2019

    Keywords

    • Back-translation
    • Code-switching
    • Machine-translation

    Fingerprint

    Dive into the research topics of 'Back-translation approach for code-switching machine translation: A case study'. Together they form a unique fingerprint.

    Cite this