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

ACL ID C14-1111
Title Morfessor FlatCat: An HMM-Based Method for Unsupervised and Semi-Supervised Learning of Morphology
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

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 hid- den Markov model structure. It builds on previous work on Morfessor, sharing model compo- nents 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 semi- supervised learning it provides state-of-the-art results in the Morpho Challenge 2010 tasks for English, Finnish, and Turkish.