Research on English Part-of-speech Tagging Based on Double-Layer Hidden Markov Model
LAI Wei
JIN Zhong
Abstract：Based on the traditional first-order hidden Markov model,this paper proposes a double-layer hidden Markov mod-el to solve the problem of incomplete structural information mining of hidden Markov model.In the process of using the Baum-Welch algorithm,the double-layer hidden Markov model regards the part-of-speech sequence as an observation sequence,and extracts more information and maximizes the probability of the part-of-speech sequence through the Baum-Welch algorithm,which is more suitable for the actual situation.made corresponding changes.The model is cross-validated with 10 folds on the Penn Treebank corpus and the Groningen Meaning Bank corpus,and compared with traditional first-order and second-order hidden Mar-kov models.The results show that the double-layer hidden Markov model has a higher accuracy of part-of-speech tagging than the traditional first-order and second-order hidden Markov models.
Keywords：hidden Markov modelBaum-Welch algorithmpart-of-speech taggingViterbi algorithmdouble-layer hid-den Markov model
Publication Date：2025-05-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1226-1229,1268 )