Back close

Kernel based part of speech tagger for kannada

Publication Type : Conference Paper

Publisher : IEEE

Source : Machine Learning and Cybernetics (ICMLC), 2010 International Conference on, IEEE, Volume 4, Qingdao, p.2139-2144 (2010)

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Electronics and Communication

Year : 2010

Abstract : The proposed paper presents the development of a part-of-speech tagger for Kannada language that can be used for analyzing and annotating Kannada texts. POS tagging is considered as one of the basic tool and component necessary for many Natural Language Processing (NLP) applications like speech recognition, natural language parsing, information retrieval and information extraction of a given language. In order to alleviate problems for Kannada language, we proposed a new machine learning POS tagger approach. Identifying the ambiguities in Kannada lexical items is the challenging objective in the process of developing an efficient and accurate POS Tagger. We have developed our own tagset which consist of 30 tags and built a part-of-speech Tagger for Kannada Language using Support Vector Machine (SVM). A corpus of texts, extracted from Kannada news papers and books, is manually morphologically analyzed and tagged using our developed tagset. The performance of the system is evaluated and we found that the result obtained was more efficient and accurate compared with earlier methods for Kannada POS tagging.

Cite this Research Publication : P. J. Antony and Dr. Soman K. P., “Kernel based part of speech tagger for kannada”, in Machine Learning and Cybernetics (ICMLC), 2010 International Conference on, Qingdao, 2010, vol. 4, pp. 2139-2144.

Admissions Apply Now