Abstract
Code-mixed text generation systems have found applications in many downstream tasks, including speech recognition, translation and dialogue. A paradigm of these generation systems relies on well-defined grammatical theories of code-mixing, and there is a lack of comparison of these theories. We present a large-scale human evaluation of two popular grammatical theories, Matrix-Embedded Language (ML) and Equivalence Constraint (EC). We compare them against three heuristic-based models and quantitatively demonstrate the effectiveness of the two grammatical theories.- Anthology ID:
- 2021.wnut-1.18
- Volume:
- Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
- Venue:
- WNUT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 158–167
- Language:
- URL:
- https://aclanthology.org/2021.wnut-1.18
- DOI:
- 10.18653/v1/2021.wnut-1.18
- Cite (ACL):
- Adithya Pratapa and Monojit Choudhury. 2021. Comparing Grammatical Theories of Code-Mixing. In Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021), pages 158–167, Online. Association for Computational Linguistics.
- Cite (Informal):
- Comparing Grammatical Theories of Code-Mixing (Pratapa & Choudhury, WNUT 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2021.wnut-1.18.pdf