Simpler unsupervised POS tagging with bilingual projections

Long Duong, Paul Cook, Steven Bird, Pavel Pecina

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

Abstract

We present an unsupervised approach to part-of-speech tagging based on projections of tags in a word-aligned bilingual parallel corpus. In contrast 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. In experimental results on eight languages, our method achieves state-of-The-art results.

Original languageEnglish
Title of host publicationProceedings of the 51st Annual Meeting of the Association for Computational Linguistics
EditorsPascale Fung, Massimo Poesio
Place of PublicationSofia, Bulgaria
PublisherAssociation for Computational Linguistics (ACL)
Pages634-639
Number of pages6
Volume2
ISBN (Print)9781937284510
Publication statusPublished - 2013
Externally publishedYes
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: 4 Aug 20139 Aug 2013

Conference

Conference51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
CountryBulgaria
CitySofia
Period4/08/139/08/13

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  • Cite this

    Duong, L., Cook, P., Bird, S., & Pecina, P. (2013). Simpler unsupervised POS tagging with bilingual projections. In P. Fung, & M. Poesio (Eds.), Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 634-639). Association for Computational Linguistics (ACL).