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Task-Specific Pre-Training and Cross Lingual Transfer for Code-Switched Data

2021-02-24 16:57:58
Akshat Gupta, Sai Krishna Rallabandi, Alan Black

Abstract

Using task-specific pre-training and leveraging cross-lingual transfer are two of the most popular ways to handle code-switched data. In this paper, we aim to compare the effects of both for the task of sentiment analysis. We work with two Dravidian Code-Switched languages - Tamil-Engish and Malayalam-English and four different BERT based models. We compare the effects of task-specific pre-training and cross-lingual transfer and find that task-specific pre-training results in superior zero-shot and supervised performance when compared to performance achieved by leveraging cross-lingual transfer from multilingual BERT models.

Abstract (translated)

URL

https://arxiv.org/abs/2102.12407

PDF

https://arxiv.org/pdf/2102.12407.pdf


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