We present an unsupervised approach to part-of-speech tagging based on projections of tags in a word-aligned bilingual parallel corpus.
to the existing state-of-the-art approach of Das and Petrov, we have developed a substantially simpler method by automatically identifying "good" training sentences from the parallel corpus and applying self-training.