Comparing Grammatical Theories of Code-Mixing

Adithya Pratapa, Monojit Choudhury


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
Venues:
EMNLP | 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
Bibkey:
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)
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PDF:
https://aclanthology.org/2021.wnut-1.18.pdf