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Can You Traducir This? Machine Translation for Code-Switched Input

Jitao Xu 1 François yvon 1 
1 TLP - Traitement du Langage Parlé
LISN - Laboratoire Interdisciplinaire des Sciences du Numérique, STL - Sciences et Technologies des Langues
Abstract : Code-Switching (CSW) is a common phenomenon that occurs in multilingual geographic or social contexts, which raises challenging problems for natural language processing tools. We focus here on Machine Translation (MT) of CSW texts, where we aim to simultaneously disentangle and translate the two mixed languages. Due to the lack of actual translated CSW data, we generate artificial training data from regular parallel texts. Experiments show this training strategy yields MT systems that surpass multilingual systems for code-switched texts. These results are confirmed in an alternative task aimed at providing contextual translations for a L2 writing assistant.
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Conference papers
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Submitted on : Monday, May 10, 2021 - 10:57:38 AM
Last modification on : Sunday, June 26, 2022 - 3:07:58 AM
Long-term archiving on: : Wednesday, August 11, 2021 - 6:08:33 PM


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  • HAL Id : hal-03218889, version 1
  • ARXIV : 2105.04846


Jitao Xu, François yvon. Can You Traducir This? Machine Translation for Code-Switched Input. Workshop on Computational Approaches to Linguistic Code Switching, Association for Computational Linguistics, Jun 2021, Online, United States. ⟨hal-03218889⟩



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