Abstract
Code-Switching is the embedding of linguistic units or phrases from two or more languages in a single sentence. This phenomenon is practiced in all multilingual communities and is prominent in social media. Consequently, there is a growing need to understand code-switched translations by translating the code-switched text into one of the standard languages or vice versa. Neural Machine translation is a well-studied research problem in the monolingual text. In this paper, we have used the gated convolutional sequences to sequence networks for English-Hinglish translation. The convolutions in the model help to identify the compositional structure in the sequences more easily. The model relies on gating and performs multiple attention steps at encoder and decoder layers.- Anthology ID:
- 2021.calcs-1.4
- Volume:
- Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Thamar Solorio, Shuguang Chen, Alan W. Black, Mona Diab, Sunayana Sitaram, Victor Soto, Emre Yilmaz, Anirudh Srinivasan
- Venue:
- CALCS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 26–30
- Language:
- URL:
- https://aclanthology.org/2021.calcs-1.4
- DOI:
- 10.18653/v1/2021.calcs-1.4
- Cite (ACL):
- Suman Dowlagar and Radhika Mamidi. 2021. Gated Convolutional Sequence to Sequence Based Learning for English-Hingilsh Code-Switched Machine Translation.. In Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching, pages 26–30, Online. Association for Computational Linguistics.
- Cite (Informal):
- Gated Convolutional Sequence to Sequence Based Learning for English-Hingilsh Code-Switched Machine Translation. (Dowlagar & Mamidi, CALCS 2021)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2021.calcs-1.4.pdf