Checks and Strategies for Enabling Code-Switched Machine Translation

• URL: http://arxiv.org/abs/2210.05096v1
• Date: Tue, 11 Oct 2022 02:25:21 GMT
• Title: Checks and Strategies for Enabling Code-Switched Machine Translation
• Authors: Thamme Gowda, Mozhdeh Gheini, Jonathan May
• Abstract summary: Code-switching is a common phenomenon among multilingual speakers, where alternation between two or more languages occurs within the context of a single conversation. This work explores multilingual neural machine translation (NMT) models' ability to handle code-switched text.
• Score: 22.67264032644644
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Code-switching is a common phenomenon among multilingual speakers, where alternation between two or more languages occurs within the context of a single conversation. While multilingual humans can seamlessly switch back and forth between languages, multilingual neural machine translation (NMT) models are not robust to such sudden changes in input. This work explores multilingual NMT models' ability to handle code-switched text. First, we propose checks to measure switching capability. Second, we investigate simple and effective data augmentation methods that can enhance an NMT model's ability to support code-switching. Finally, by using a glass-box analysis of attention modules, we demonstrate the effectiveness of these methods in improving robustness.

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