2022
EMNLP
EMNLP 2022
On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish
Abstract
AbstractPerformance of downstream NLP tasks on code-switched Hindi-English (aka ) continues to remain a significant challenge. Intuitively, Hindi and English corpora should aid improve task performance on Hinglish. We show that meta-learning framework can effectively utilize the the labelled resources of the downstream tasks in the constituent languages. The proposed approach improves the performance on downstream tasks on code-switched language. We experiment with code-switching benchmark GLUECoS and report significant improvements.
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Interdisciplinary Bridge
- Artificial Intelligence and Interdisciplinary and Natural Language Processing
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Hot Topic Early Bird
- low-resource language