DesiPayanam: developing an Indic travel partner

Diviya K N, Mrinalini K, Vijayalakshmi P, Thenmozhi J, Nagarajan T


Abstract
Domain-specific machine translation (MT) systems are essential in bridging the communication gap between people across different businesses, economies, and countries. India, a linguistically rich country with a booming tourism industry is a perfect market for such an MT system. On this note, the current work aims to develop a domain-specific transformer-based MT system for Hindi-to-Tamil translation. In the current work, neural-based MT (NMT) model is trained from scratch and the hyper-parameters of the model architecture are modified to analyze its effect on the translation performance. Further, a finetuning approach is adopted to finetune a pretrained transformer MT model to better suit the tourism domain. The proposed experiments are observed to improve the BLEU scores of the translation system by a maximum of 1% and 4% for the training from scratch and finetuned systems respectively.
Anthology ID:
2024.icon-1.97
Volume:
Proceedings of the 21st International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2024
Address:
AU-KBC Research Centre, Chennai, India
Editors:
Sobha Lalitha Devi, Karunesh Arora
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
480–484
Language:
URL:
https://preview.aclanthology.org/icon-24-ingestion/2024.icon-1.97/
DOI:
Bibkey:
Cite (ACL):
Diviya K N, Mrinalini K, Vijayalakshmi P, Thenmozhi J, and Nagarajan T. 2024. DesiPayanam: developing an Indic travel partner. In Proceedings of the 21st International Conference on Natural Language Processing (ICON), pages 480–484, AU-KBC Research Centre, Chennai, India. NLP Association of India (NLPAI).
Cite (Informal):
DesiPayanam: developing an Indic travel partner (K N et al., ICON 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/icon-24-ingestion/2024.icon-1.97.pdf