A Statistical Method for Evaluating Performance of Part of Speech Tagger for Gujarati | Zendy

Pooja Bhatt | Zendy; Amit Ganatra | Zendy

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A Statistical Method for Evaluating Performance of Part of Speech Tagger for Gujarati

Author(s) -

Pooja Bhatt,

Amit Ganatra

Publication year - 2019

Publication title -

international journal of recent technology and engineering (ijrte)

Language(s) - English

Resource type - Journals

ISSN - 2277-3878

DOI - 10.35940/ijrte.b1492.078219

Subject(s) - gujarati , computer science , natural language processing , part of speech tagging , set (abstract data type) , hidden markov model , artificial intelligence , speech recognition , part of speech , linguistics , philosophy , programming language

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.

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