Zero-Shot Hate to Non-Hate Text Conversion Using Lexical Constraints

Bibliographic Data

ID22108406
AuthorsZishan Ahmad (0000-0001-6170-4608, Indian Institute of Technology Patna), Vinnakota Sai Sujeeth (0000-0002-0130-2217, Tejas Networks (India)), Asif Ekbal (0000-0003-3612-8834, Indian Institute of Technology Patna)
Year2023
Volume10
Issue5
Pages2479-2488
Publication date2023-10-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2022.3175259
OpenAlexW4293195510
LanguageEN
Citations received2
References cited17

Systems meant for tackling hate speech have been increasing in demand with the rapid growth of social media platforms. One way of controlling hate speech in texts is to transform the text into its non-hate version while preserving the rest of the contents. Without the use of parallel data, unsupervised back-translation-based text style transfer is a common method of tackling such problems. In this article, we propose a zero-shot style-transfer technique that does effective unsupervised hate to non-hate conversion without using any hate domain text for training. While decoding the outputs produced by the system, we define an additional step of introducing lexical constraints, for better preservation of contents. Detailed empirical evaluation shows that the zero-shot method outperforms classical unsupervised style-transfer methods while at the same time reducing the data required while training

Algorithm · Decoding methods · Linguistics · Natural language processing · Social media · Speech recognition · World Wide Web · Cancer-related gene regulation · Computer Science · Hate Speech and Cyberbullying Detection · Artificial Intelligence

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