A hidden Markov model for Persian part-of-speech tagging
Morteza Okhovvat, Behrouz Minaei Bidgoli · Procedia Computer Science · 2011
One of the important actions in the processing of languages is part-of-speech tagging. Against of this importance, although numerous models have been presented in different languages but there is few works have been done in Persian language. In this paper, a part-of-speech tagging system on Persian corpus by using hidden Markov model is proposed. Achieving to this goal, the main aspects of Persian morphology is introduced and developed. To evaluate the accuracy of proposed approach, this approach is applied in simulations which are done on both homogeneous and heterogeneous Persian corpus. Getting results with 98.1% accuracy in the experiments demonstrate the suitable efficiency of the proposed approach on Persian corpus.