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Learnability in Optimality Theory
, 1995
"... In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given gr ..."
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Cited by 447 (33 self)
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In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given grammatical module. We decompose the learning problem and present formal results for a central subproblem, deducing the constraint ranking particular to a target language, given structural descriptions of positive examples. The structure imposed on the space of possible grammars by Optimality Theory allows efficient convergence to a correct grammar. We discuss implications for learning from overt data only, as well as other learning issues. We argue that Optimality Theory promotes confluence of the demands of more effective learnability and deeper linguistic explanation.
A maximum entropy model of phonotactics and phonotactic learning
, 2006
"... The study of phonotactics (e.g., the ability of English speakers to distinguish possible words like blick from impossible words like *bnick) is a central topic in phonology. We propose a theory of phonotactic grammars and a learning algorithm that constructs such grammars from positive evidence. Our ..."
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Cited by 87 (13 self)
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The study of phonotactics (e.g., the ability of English speakers to distinguish possible words like blick from impossible words like *bnick) is a central topic in phonology. We propose a theory of phonotactic grammars and a learning algorithm that constructs such grammars from positive evidence. Our grammars consist of constraints that are assigned numerical weights according to the principle of maximum entropy. Possible words are assessed by these grammars based on the weighted sum of their constraint violations. The learning algorithm yields grammars that can capture both categorical and gradient phonotactic patterns. The algorithm is not provided with any constraints in advance, but uses its own resources to form constraints and weight them. A baseline model, in which Universal Grammar is reduced to a feature set and an SPEstyle constraint format, suffices to learn many phonotactic phenomena. In order to learn nonlocal phenomena such as stress and vowel harmony, it is necessary to augment the model with autosegmental tiers and metrical grids. Our results thus offer novel, learningtheoretic support for such representations. We apply the model to English syllable onsets, Shona vowel harmony, quantityinsensitive stress typology, and the full phonotactics of Wargamay, showing that the learned grammars capture the distributional generalizations of these languages and accurately predict the findings of a phonotactic experiment.
Optimality theory and the generative complexity of constraint violability
 Computational Linguistics
, 1998
"... It has been argued that rulebased phonological descriptions can uniformly be expressed as mappings carried out by finitestate transducers, and therefore fall within the class of rational relations. If this property of generative capacity is an empirically correct characterization of phonological ..."
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Cited by 81 (2 self)
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It has been argued that rulebased phonological descriptions can uniformly be expressed as mappings carried out by finitestate transducers, and therefore fall within the class of rational relations. If this property of generative capacity is an empirically correct characterization of phonological mappings, it should hold of any sufficiently restrictive theory of phonology, whether it utilizes constraints or rewrite rules. In this paper, we investigate the conditions under which the phonological descriptions that are possible within the view of constraint interaction embodied in Optimality Theory (Prince and Smolensky 1993) remain within the class of rational relations. We show that this is true when GEN is itself a rational relation, and each of the constraints distinguishes among finitely many regular sets of candidates. 1.
The Proper Treatment of Optimality in Computational Phonology
 Bilkent University
, 1998
"... This paper presents a novel forrealization of optimality theory. Unlike pre yions treatments of optimality in computational linguistics, starting with Ellison (1994), the new approach does not require any explicit marking and counting of constraint violations. It is based on the notion of "len ..."
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Cited by 67 (8 self)
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This paper presents a novel forrealization of optimality theory. Unlike pre yions treatments of optimality in computational linguistics, starting with Ellison (1994), the new approach does not require any explicit marking and counting of constraint violations. It is based on the notion of "lenient composition", defined as the combination of ordinary composition and priority union. If an underlying form has outputs that can meet a given constraint, lenient composition enforces the constraint; ff none of the output candidates meets the constraint, lenient composition allows all of them. For the sake of greater efficiency, we may "eniently compose" the a. relation and all the constraints into a single finitestate transducer that maps each underlying form directly into its op timal surface realizations, and vice versa.. Seen from this perspective, optimality theory is surprisingly similar to the two older strains of finitestate phonology: classical rewrite systems and twolevel models. In particular, the ranking of optimality constraints corresponds to the ordering of rewrite rules.
Declarative Phonology
 PROCEEDINGS OF THE XVTH INTERNATIONAL CONGRESS OF LINGUISTS. UNIVERSITÉ LAVAL, QUÉBEC
, 1992
"... Declarative phonology is a program of research that was motivated in part by the need for theories of phonology that can be implemented on a computer. While it is clear that such a development would be beneficial for both theoretical and field phonology, it is not immediately obvious how one should ..."
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Cited by 45 (4 self)
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Declarative phonology is a program of research that was motivated in part by the need for theories of phonology that can be implemented on a computer. While it is clear that such a development would be beneficial for both theoretical and field phonology, it is not immediately obvious how one should go about implementing phonological models. The
Learning bias and phonologicalrule induction
 Computational Linguistics
, 1996
"... A fundamental debate in the machine learning of language has been the role of prior knowledge in the learning process. Purely nativist approaches, such as the Principles and Parameters model, build parameterized linguistic generalizations directly into the learning system. Purely empirical approache ..."
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Cited by 31 (0 self)
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A fundamental debate in the machine learning of language has been the role of prior knowledge in the learning process. Purely nativist approaches, such as the Principles and Parameters model, build parameterized linguistic generalizations directly into the learning system. Purely empirical approaches use a general, domainindependent learning rule (Error BackPropagation, Instancebased Generalization, Minimum Description Length) to learn linguistic generalizations directly from the data. In this paper we suggest that an alternative to the purely nativist or purely empiricist learning paradigms is to represent the prior knowledge of language as a set of abstract learning biases, which guide an empirical inductive learning algorithm. We test our idea by examining the machine learning of simple Sound Pattern of English ( S P E)style phonological rules. We represent phonological rules as finitestate transducers that accept underlying forms as input and generate surface forms as output. We show that OSTIA, a generalpurpose transducer induction algorithm, was incapable of learning simple phonological rules like flapping. We then augmented OSTIA with three kinds of learning biases that are specific to natural language phonology, and that are assumed explicitly or implicitly by every theory of phonology: faithfulness (underlying segments
Evaluation, Implementation, and Extension of Primitive Optimality Theory
, 1997
"... Eisner's (1997a) Primitive Optimality Theory is a simple formal model of a subset of Optimality Theory (Prince and Smolensky 1993). The work presented here implements this model and extends it. The implementation is used to evaluate the Primitive Optimality Theory model, and is in itself a usef ..."
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Cited by 30 (4 self)
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Eisner's (1997a) Primitive Optimality Theory is a simple formal model of a subset of Optimality Theory (Prince and Smolensky 1993). The work presented here implements this model and extends it. The implementation is used to evaluate the Primitive Optimality Theory model, and is in itself a useful tool for linguistic analysis. The model is evaluated in terms of its success or failure as an attempt to formulate a cognitively plausible, computationally tractable, and mathematically formal model of the Optimality Theoretic framework of phonological theory. As part of this evaluation, a comprehensive, implemented analysis is given for the harmony and disharmony phenomena of Turkish. In addition to an evaluation of the Primitive Optimality Theory model, concrete proposals are suggested for possible extensions to the model, and for improved models that, unlike Primitive Optimality Theory, can model nonconcatenative morphology, Paradigm Uniformity, and reduplication.
Computing Optimal Forms in Optimality Theory: Basic Syllabification. Ms
, 1995
"... In Optimality Theory, grammaticality is defined in terms of optimization over a large (often infinite) space of candidates. This raises the question of how grammatical forms might be computed. This paper presents an analysis of the Basic CV Syllable Theory (Prince & Smolensky 1993) showing that, ..."
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Cited by 26 (7 self)
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In Optimality Theory, grammaticality is defined in terms of optimization over a large (often infinite) space of candidates. This raises the question of how grammatical forms might be computed. This paper presents an analysis of the Basic CV Syllable Theory (Prince & Smolensky 1993) showing that, despite the nature of the formal definition, computing the optimal form does not require explicitly generating and evaluating all possible candidates. A specific algorithm is detailed which computes the optimal form in time that is linear in the length of the input. This algorithm will work for any grammar in Optimality Theory employing regular position structures and universal constraints which may be evaluated on the basis of local information. Computing Optimal Forms In Optimality Theory: Basic Syllabification
Model theory and the content of OT constraints
, 2002
"... We develop an extensible description logic for stating the content of optimalitytheoretic constraints in phonology, and specify a class of structures for interpreting it. The aim is a transparent formalisation of OT. We show how to state a wide range of constraints, including markedness, input–outpu ..."
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Cited by 24 (3 self)
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We develop an extensible description logic for stating the content of optimalitytheoretic constraints in phonology, and specify a class of structures for interpreting it. The aim is a transparent formalisation of OT. We show how to state a wide range of constraints, including markedness, input–output faithfulness and base–reduplicant faithfulness. However, output–output correspondence and ‘intercandidate’ sympathy are revealed to be problematic: it is unclear that any reasonable class of structures can reconstruct their proponents’ intentions. But our contribution is positive. Proponents of both output–output correspondence and sympathy have offered alternatives that fit into the general OT picture. We show how to state these in a reasonable extension of our formalism. The problematic constraint types were developed to deal with opaque phenomena. We hope to shed new light on the debate about how to handle opacity, by subjecting some common responses to it within OT to critical investigation.