Investigating language independence in HMM PoS/MSD-tagging

The paper presents an investigation of functional dependencies in morphosyntactic tagging using hidden Markov models. Starting from a well known fact that the HMM tagging paradigm relies on lexical knowledge acquired from training corpora and stored in form of transition and emission matrices, also called a language model, in the experiment, we apply the TnT trigram tagger on creating language models for seven different languages from MULTEXT East version 3 project translations of George Orwellpsilas novel 1984. - Czech, Estonian, Hungarian, Romanian, Serbian, Slovene and original English version. We then use these language models in the tagging procedure and obtain details on various relations between training corpora statistics, training outputs and outputs of the tagging procedure.