Publisher : International Journal of Applied Engineering Research
Campus : Kochi
School : School of Arts and Sciences
Department : Computer Science
Year : 2015
Abstract : Hidden Markov Model (HMM) is one of the efficient methods for Parts Of Speech Tagging. In this paper we propose to introduce an enhanced POS Tagger for English sentences using HMM Bigram model. As part of implementation, we are using our own Tag Set and a supervised sentence corpus. Most accurate tag sequence for the sentence is decoded using Viterbi Algorithm. We are using our own replication algorithm to check sentences with similar tag sequences and expand the corpus with newly learned sentences. © Research India Publications.