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.
The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges
A survey of code-switching research in natural language processing, covering methodologies, challenges, and future directions.
- Year
- 2022
- Venue
- arXiv 2022
- Authors
- 4
- Hosting
- Abstract onlyARXIV-DEFAULT
Cite
Notes
Only stored in your browser.
Attribution
- Abstract & full text
- arxiv.org/abs/2212.09660v2ARXIV-DEFAULT
- TL;DR
- Semantic Scholar