Samvaadhana: A Telugu Dialogue System in Hospital Domain

Suma Reddy Duggenpudi, Kusampudi Siva Subrahamanyam Varma, Radhika Mamidi


Abstract
In this paper, a dialogue system for Hospital domain in Telugu, which is a resource-poor Dravidian language, has been built. It handles various hospital and doctor related queries. The main aim of this paper is to present an approach for modelling a dialogue system in a resource-poor language by combining linguistic and domain knowledge. Focusing on the question answering aspect of the dialogue system, we identified Question Classification and Query Processing as the two most important parts of the dialogue system. Our method combines deep learning techniques for question classification and computational rule-based analysis for query processing. Human evaluation of the system has been performed as there is no automated evaluation tool for dialogue systems in Telugu. Our system achieves a high overall rating along with a significantly accurate context-capturing method as shown in the results.
Anthology ID:
D19-6126
Volume:
Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Colin Cherry, Greg Durrett, George Foster, Reza Haffari, Shahram Khadivi, Nanyun Peng, Xiang Ren, Swabha Swayamdipta
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
234–242
Language:
URL:
https://aclanthology.org/D19-6126
DOI:
10.18653/v1/D19-6126
Bibkey:
Cite (ACL):
Suma Reddy Duggenpudi, Kusampudi Siva Subrahamanyam Varma, and Radhika Mamidi. 2019. Samvaadhana: A Telugu Dialogue System in Hospital Domain. In Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), pages 234–242, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Samvaadhana: A Telugu Dialogue System in Hospital Domain (Duggenpudi et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-6126.pdf