Automatic POS Tagging of Bhojpuri: A Comparative Study with Hindi

This work is one of the initial experiments towards creating the automatic Part-of Speech (POS) tagger for Bhojpuri language. Bhojpuri is a lesser resource language and does not have much technology available therefore this work presents the first big representative Bhojpuri corpus of approx 267000 tokens from different domains and a SVM (Support Vector Machine) based POS tagger trained on this corpus. The accuracy of the tagger achieved under this experiment is approx. 87 %. This work also cover a detail guideline of annotating Bhojpuri corpus following BIS scheme and a comparative analysis of performances of Bhojpuri and Hindi POS taggers trained with SVM model.