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

Jitao Xu, François Yvon


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.
Anthology ID:
2021.calcs-1.11
Volume:
Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching
Month:
June
Year:
2021
Address:
Online
Venues:
CALCS | NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
84–94
Language:
URL:
https://aclanthology.org/2021.calcs-1.11
DOI:
10.18653/v1/2021.calcs-1.11
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.calcs-1.11.pdf