Morfessor FlatCat: An HMM-Based Method for Unsupervised and Semi-Supervised Learning of Morphology

نویسندگان

  • Stig-Arne Grönroos
  • Sami Virpioja
  • Peter Smit
  • Mikko Kurimo
چکیده

Morfessor is a family of methods for learning morphological segmentations of words based on unannotated data. We introduce a new variant of Morfessor, FlatCat, that applies a hidden Markov model structure. It builds on previous work on Morfessor, sharing model components with the popular Morfessor Baseline and Categories-MAP variants. Our experiments show that while unsupervised FlatCat does not reach the accuracy of Categories-MAP, with semisupervised learning it provides state-of-the-art results in the Morpho Challenge 2010 tasks for English, Finnish, and Turkish.

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تاریخ انتشار 2014