Handling Reduplication in a Morphological Analyzer for Wamesa
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2020
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Haverford College. Department of Computer Science
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Thesis
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Award
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eng
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Open Access
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Abstract
This thesis seeks to assess previous computational work done regarding reduplication in order to account for reduplication in a morphological analyzer for the Wamesa language. This paper includes a brief introduction to Wamesa, reduplication, two-level rules, and morphological analysis. The use of finite-state transducers as morphological analyzers is also discussed. Additionally, various methods that researchers have used to deal with reduplication in computational models are evaluated. Methods include the use of two-level rules and supplementing finite-state transducers with an equality operator, memory devices, and bidirectional reading capabilities. Ultimately, I propose additions and modifications to the Wamesa morphological analyzer, which involves the use of the Helsinki Finite-State Toolkit and two-level rules.