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.
Item Type:	Article
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Computer Architecture for Embedded Systems (CAES)
Link to this item:	http://purl.utwente.nl/publications/63349
Official URL:	http://www.vtex.lt/Informatica/htm/INFO543.htm
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