A statistical HMM(Hidden Markov Model) part-of-speech tagging apparatus and method capable of being applied to a new domain without a tagged domain corpus are provided to select a lexicon with lexical probability varied according to a domain to which the lexicon is applied, and update the lexical probability according to the domain to improve tagging accuracy without having a tagged domain corpus in a specific domain. Tagging probability information is learnt from a previously tagged corpus to construct a lexical/part-of-speech/contextual probability information database and a lexical probability information database(S210). The lexical probability information database is domain-dependently leant and updated based on a raw corpus of an application domain(S220). Morpheme analysis is performed on an input sentence on the basis of a morpheme analysis dictionary database(S240). Statistical part-of-speech tagging is carried out on the morpheme analysis result based on the lexical/part-of-speech/contextual probability information database and the updated lexical probability information database(S250). An error in the tagging result is corrected according to a tagging error correction rule database(S260).
Method and apparatus for statistical HMM part-of-speech tagging without tagged domain corpus