Abstract
In this paper I present a novel Machine Learning approach to the acquisition of stochastic string transductions based on Pair Hidden Markov Models (PHMMs), a model used in computational biology. I show how these models can be used to learn morphological processes in a variety of languages, including English, German and Arabic. Previous techniques for learning morphology have been restricted to languages with essentially concatenative morphology.
Original language | English |
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Title of host publication | Proceedings of the Association for Computational Linguistics |
Subtitle of host publication | Student Session |
Pages | 55-60 |
Publication status | Published - 1 Jul 2001 |