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Parts of Speech Tagging for Indic Languages: A Survey

Floyd Avina Fernandes1 , Kavita Asnani2

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 729-736, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.729736

Online published on Mar 31, 2019

Copyright © Floyd Avina Fernandes, Kavita Asnani . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Floyd Avina Fernandes, Kavita Asnani, “Parts of Speech Tagging for Indic Languages: A Survey,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.729-736, 2019.

MLA Style Citation: Floyd Avina Fernandes, Kavita Asnani "Parts of Speech Tagging for Indic Languages: A Survey." International Journal of Computer Sciences and Engineering 7.3 (2019): 729-736.

APA Style Citation: Floyd Avina Fernandes, Kavita Asnani, (2019). Parts of Speech Tagging for Indic Languages: A Survey. International Journal of Computer Sciences and Engineering, 7(3), 729-736.

BibTex Style Citation:
@article{Fernandes_2019,
author = {Floyd Avina Fernandes, Kavita Asnani},
title = {Parts of Speech Tagging for Indic Languages: A Survey},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {729-736},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3908},
doi = {https://doi.org/10.26438/ijcse/v7i3.729736}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.729736}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3908
TI - Parts of Speech Tagging for Indic Languages: A Survey
T2 - International Journal of Computer Sciences and Engineering
AU - Floyd Avina Fernandes, Kavita Asnani
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 729-736
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Natural language processing (NLP) comprises of various techniques addressing language text. Few to mention are Part of Speech (POS) tagger, Chunker, Morphological Analyzer, Spell-Checkers, Grammar Checkers, Machine translator, Transliterator etc. POS tagging is the basic building block in language processing which assigns part of Speech (POS) tag which is a peculiar label assigned to each and every token (word) in a text corpus to indicate the part of speech such as verb, pronoun, noun, adjective etc. POS tagging is useful and significant in pre-processing phase especially in the area of information retrieval, text to speech processing, word sense disambiguation and information processing. The methods of POS tagging are classified as rule-based POS tagging, transformation-based tagging, and stochastic tagging. Recent research reports various methods and approaches like Markov Model (MM), SVM (Support Vector Machine), ME (Maximum Entropy) etc used for POS tagging tested on several Indic languages like Hindi, Bengali, Manipuri, Assamese, Telugu, Kannada, Malayalam, Tamil, Punjabi. Since the performance of POS taggers is specific to context and language, there is a pressing need to carry out exhaustive survey. . This paper highlights a comprehensive study on two indic languages i.e. Hindi and Bengali. POS taggers with various approaches along with performance are reported.

Key-Words / Index Term

Ambiguity, Natural language processing (NLP), Named Entity Recognition (NER), Part of Speech(POS), Tagger

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