Evaluating Sequence Alignment for Learning Inflectional Morphology
David King · 2016
This work examines CRF-based sequence alignment models for learning natural language morphology.Although these systems have performed well for a limited number of languages, this work, as part of the SIGMORPHON 2016 shared task, specifically sets out to determine whether these models handle non-concatenative morphology as well as previous work might suggest.Results, however, indicate a strong preference for simpler, concatenative morphological systems.