Open AccessA Statistical Method for Evaluating Performance of Part of Speech Tagger for Gujarati
Author(s) -
Pooja M Bhatt,
Amit Ganatra
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1492.078219
Subject(s) - gujarati , computer science , natural language processing , set (abstract data type) , hidden markov model , artificial intelligence , speech recognition , part of speech tagging , part of speech , linguistics , programming language , philosophy
Part of Speech Tagging has continually been a difficult mission in the era of Natural Language Processing. This article offers POS tagging for Gujarati textual content the use of Hidden Markov Model. Using Gujarati text annotated corpus for training checking out statistics set are randomly separated. 80% accuracy is given by model. Error analysis in which the mismatches happened is likewise mentioned in element.