Designing HMM-based part-of-speech tagger for Lithuanian language


Pajarskaite, G. and Griciute, V. and Raskinis, G. and Kuper, J. (2004) Designing HMM-based part-of-speech tagger for Lithuanian language. Informatica, 15 (2). pp. 231-242. ISSN 0868-4952

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Abstract:This paper describes a preliminary experiment in designing a Hidden Markov Model (HMM)-based part-of-speech tagger for the Lithuanian language. Part-of-speech tagging is the problem of assigning to each word of a text the proper tag in its context of appearance. It is accomplished in two basic steps: morphological analysis and disambiguation. In this paper, we focus on the problem of disambiguation, i.e., on the problem of choosing the correct tag for each word in the context of a set of possible tags. We constructed a stochastic disambiguation algorithm, based on supervised learning techniques, to learn hidden Markov model's parameters from hand-annotated corpora. The Viterbi algorithm is used to assign the most probable tag to each word in the text.
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Electrical Engineering, Mathematics and Computer Science (EEMCS)
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