Approximation and Exactness in Finite State Optimality Theory
Dale Gerdemann, Gertjan van Noord
TL;DR
This paper introduces a new finite-state approach to gradient constraints in Optimality Theory, achieving exact and compact analysis for syllabification, improving upon previous approximation methods.
Contribution
It presents a novel finite-state treatment of gradient constraints that is both exact and more compact than prior approximations.
Findings
The new method is exact for syllabification analysis.
It significantly improves the approximation of previous models.
The approach is compact and computationally efficient.
Abstract
Previous work (Frank and Satta 1998; Karttunen, 1998) has shown that Optimality Theory with gradient constraints generally is not finite state. A new finite-state treatment of gradient constraints is presented which improves upon the approximation of Karttunen (1998). The method turns out to be exact, and very compact, for the syllabification analysis of Prince and Smolensky (1993).
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Taxonomy
TopicsBlind Source Separation Techniques · Algorithms and Data Compression · Logic, programming, and type systems