no code implementations • PAIL (ICON) 2021 • Vijay Sundar Ram, Sobha Lalitha Devi
In this paper, we discuss the development of a dependency parser for Tamil, a South Dravidian language.
no code implementations • WILDRE (LREC) 2022 • Treesa Cyriac, Sobha Lalitha Devi
The classification and features are given and are studied using Malayalam multiwords.
no code implementations • WILDRE (LREC) 2022 • Kumari Sheeja S, Sobha Lalitha Devi
This work presents an automatic identification of explicit connectives and its arguments using supervised method, Conditional Random Fields (CRFs).
no code implementations • LREC 2020 • Malarkodi C.S, Sobha Lalitha Devi
The machine learning technique CRFs was used for the system development.
no code implementations • LREC 2020 • Vijay Sundar Ram, Sobha Lalitha Devi
Natural language understanding by automatic tools is the vital requirement for document processing tools.
no code implementations • RANLP 2019 • Sobha Lalitha Devi
The source language, which is resource rich language in this study, is Tamil and the resource poor language is Malayalam, both belonging to the same language family, Dravidian.
no code implementations • WS 2016 • Sindhuja Gopalan, Sobha Lalitha Devi
The previous works on discourse analysis in bio-medical data have concentrated only on the identification of connectives and hence we have developed an end-end parser for connective and argument identification using Conditional Random Fields algorithm.