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Improving Morphology Induction by Learning Spelling Rules
| Citations: | 7 - 0 self |
BibTeX
@MISC{Naradowsky_improvingmorphology,
author = {Jason Naradowsky},
title = {Improving Morphology Induction by Learning Spelling Rules},
year = {}
}
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Abstract
Unsupervised learning of morphology is an important task for human learners and in natural language processing systems. Previous systems focus on segmenting words into substrings (taking ⇒ tak.ing), but sometimes a segmentation-only analysis is insufficient (e.g., taking may be more appropriately analyzed as take+ing, with a spelling rule accounting for the deletion of the stem-final e). In this paper, we develop a Bayesian model for simultaneously inducing both morphology and spelling rules. We show that the addition of spelling rules improves performance over the baseline morphology-only model. 1
