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Reseach Article

Kannada Part-Of-Speech Tagging with Probabilistic Classifiers

by Shambhavi B R, Ramakanth Kumar P
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 17
Year of Publication: 2012
Authors: Shambhavi B R, Ramakanth Kumar P
10.5120/7442-0452

Shambhavi B R, Ramakanth Kumar P . Kannada Part-Of-Speech Tagging with Probabilistic Classifiers. International Journal of Computer Applications. 48, 17 ( June 2012), 26-30. DOI=10.5120/7442-0452

@article{ 10.5120/7442-0452,
author = { Shambhavi B R, Ramakanth Kumar P },
title = { Kannada Part-Of-Speech Tagging with Probabilistic Classifiers },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 17 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number17/7442-0452/ },
doi = { 10.5120/7442-0452 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:44:21.090080+05:30
%A Shambhavi B R
%A Ramakanth Kumar P
%T Kannada Part-Of-Speech Tagging with Probabilistic Classifiers
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 17
%P 26-30
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Part-Of-Speech (POS) tagging is defined as the Natural Language Processing (NLP) task in which each word in a sentence is labeled with a tag indicating its appropriate part of speech. Of the entire supervised machine learning classification algorithms, second order Hidden Markov Model (HMM) and Conditional Random Fields (CRF) is chosen in this work for POS tagging of Kannada language. Training data includes 51,269 words and test data consists of around 2932 tokens. Both set being disjoint and taken from EMILLE corpus. Experiments show that the accuracy of the tools based on HMM and CRF is 79. 9% and 84. 58% respectively.

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Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Part Of Speech Tagging Hidden Markov Model Conditional Random Fields