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Assigning automatically Part-of-Speech tags to build tagged corpus for Myanmar language
http://hdl.handle.net/20.500.12678/0000003376
http://hdl.handle.net/20.500.12678/000000337676cffad4-65a8-47f2-b498-2696fe074cc6
17f0e4b1-bee3-4f04-84e8-27d66e2dc4ad
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psc2010paper (194).pdf (193 Kb)
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Title | ||||||
Title | Assigning automatically Part-of-Speech tags to build tagged corpus for Myanmar language | |||||
Language | en | |||||
Publication date | 2010-12-16 | |||||
Authors | ||||||
Myint, Phyu Hninn | ||||||
Description | ||||||
A variety of Natural Language Processing (NLP)tasks, such as named entity recognition, stemming,question answering and machine translation, benefitfrom knowledge of the words syntactic categories orPart-of-Speech (POS). POS taggers must besuccessfully applied to assign a single best POS toevery word in a corpus.This paper presents to developPart-of-Speech tagged text corpora by employingBigram part-of-speech tagger. POS tagging is aprocess of assigning appropriate syntactic categoriesto each word in a sentence. As applying bigram modelfor automated tagging process we have provided anadequate annotated corpus from scratch. We have usedcustomized POS tagset to annotate the words in aMyanmar sentence. Our Bigram tagger has twophases: training with Hidden Markov Models (HMM)and decoding with Viterbi algorithm. | ||||||
Keywords | ||||||
Natural Language Processing, Part-of- Speech Tagging, Hidden Markov Models and Viterbi | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1133 | |||||
Journal articles | ||||||
Fifth Local Conference on Parallel and Soft Computing | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |