The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges
Genta Winata, Alham Fikri Aji, Zheng Xin Yong, Thamar Solorio
Abstract
Code-Switching, a common phenomenon in written text and conversation, has been studied over decades by the natural language processing (NLP) research community. Initially, code-switching is intensively explored by leveraging linguistic theories and, currently, more machine-learning oriented approaches to develop models. We introduce a comprehensive systematic survey on code-switching research in natural language processing to understand the progress of the past decades and conceptualize the challenges and tasks on the code-switching topic. Finally, we summarize the trends and findings and conclude with a discussion for future direction and open questions for further investigation.- Anthology ID:
- 2023.findings-acl.185
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2023
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2936–2978
- Language:
- URL:
- https://aclanthology.org/2023.findings-acl.185
- DOI:
- 10.18653/v1/2023.findings-acl.185
- Cite (ACL):
- Genta Winata, Alham Fikri Aji, Zheng Xin Yong, and Thamar Solorio. 2023. The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges. In Findings of the Association for Computational Linguistics: ACL 2023, pages 2936–2978, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges (Winata et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2023.findings-acl.185.pdf