Abstract
This paper discusses the details of submission made by team Translation Techies to the Shared Task on Machine Translation in Dravidian languages- ACL 2022. In connection to the task, five language pairs were provided to test the accuracy of submitted model. A baseline transformer model with Neural Machine Translation(NMT) technique is used which has been taken directly from the OpenNMT framework. On this baseline model, tokenization is applied using the IndicNLP library. Finally, the evaluation is performed using the BLEU scoring mechanism.- Anthology ID:
- 2022.dravidianlangtech-1.19
- Volume:
- Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Anand Kumar Madasamy, Parameswari Krishnamurthy, Elizabeth Sherly, Sinnathamby Mahesan
- Venue:
- DravidianLangTech
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 120–124
- Language:
- URL:
- https://aclanthology.org/2022.dravidianlangtech-1.19
- DOI:
- 10.18653/v1/2022.dravidianlangtech-1.19
- Cite (ACL):
- Piyushi Goyal, Musica Supriya, Dinesh U, and Ashalatha Nayak. 2022. Translation Techies @DravidianLangTech-ACL2022-Machine Translation in Dravidian Languages. In Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages, pages 120–124, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Translation Techies @DravidianLangTech-ACL2022-Machine Translation in Dravidian Languages (Goyal et al., DravidianLangTech 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2022.dravidianlangtech-1.19.pdf