Learning Morphology with Pair Hidden Markov Models

Alexander Clark

Learning Morphology with Pair Hidden Markov Models

Philosophy

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

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	Undefined/Unknown
Title of host publication	Proc. of the Student Workshop at the 39th Annual Meeting of the Association for Computational Linguistics
Pages	55-60
Number of pages	6
Publication status	Published - 1 Jul 2001

Cite this

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title = "Learning Morphology with Pair Hidden Markov Models",

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.",

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