Indian Journal of Science and Technology
Year: 2017, Volume: 10, Issue: 13, Pages: 1-11
Sasi Raja Sekhar Dokkara1*, Suresh Varma Penumathsa1 and Somayajulu G. Sripada2
1Department of Computer Science, Adikavi Nannayya University, Rajah Rajah Narendhra Nagar, East Godavari, Rajahmundry - 533296, Andhra Pradesh, India, [email protected], [email protected] 2Department of Computing Science, University of Aberdeen, UK, [email protected]
*Author for correspondence
Sasi Raja Sekhar Dokkara
Department of Computer Science, Adikavi Nannayya University, Rajah Rajah Narendhra Nagar, East Godavari, Rajahmundry - 533296, Andhra Pradesh, India, [email protected]
Objectives: The current work is a morphological generation engine that generates the required inflected Telugu verb form from an input specification consisting of lexicalized grammatical constituents and associated features. Methods/Statistical Analysis: The method employed in this paper is based on finite state techniques to develop a computational model for morphological generation of verbs in Telugu. The current work is a module of a surface realization engine for Telugu, a java application developed for generation of well-formed Telugu sentences. Test samples were taken from grammar text books for Telugu language and tested thoroughly with various alternatives of the subject with respect to person, number and gender. Findings: The evaluation was performed on a small data set because bigger authentic data sets were not available online. Hence the findings cannot be generalized but the results show that the verbs are not evenly distributed across all the classes. The results also show that no verbs were found belonging to some of the classes which means verbs belonging to those classes are not regularly used. The findings cannot be compared with any other results published because very little work was done previously in this area of research in Telugu language. The evaluation report clearly suggests that instead of going for complete coverage of verbs better to extend the coverage based on utility in NLG systems. Application/Improvements: The current work has its application in general purpose surface realization engines and machine translation systems. We intend to create a generalized morphology engine which generates the required word form for Telugu words.
Keywords: Finite Automata, Morphological Generator, Morphophonemic Group, Natural Language Generation, Personal Suffix, Tense Mode Suffix, Verb Class, Verb Forms
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