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Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection
May 05, 2020 ยท Declared Dead ยท ๐ Annual Meeting of the Association for Computational Linguistics
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Authors
Srijan Bansal, Vishal Garimella, Ayush Suhane, Jasabanta Patro, Animesh Mukherjee
arXiv ID
2005.02295
Category
cs.CL: Computation & Language
Citations
28
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
In this paper we demonstrate how code-switching patterns can be utilised to improve various downstream NLP applications. In particular, we encode different switching features to improve humour, sarcasm and hate speech detection tasks. We believe that this simple linguistic observation can also be potentially helpful in improving other similar NLP applications.
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