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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 529 (35 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.
Some aspects of optimality in natural language interpretation
- Journal of Semantics
, 2000
"... In a series of papers, Petra Hendriks, Helen de Hoop, and Henriette de Swart Lave applied optimality theory (OT) to semantics. These authors argue that there is a fundamental difference between the form of OT as used in syntax on the one hand and its form as used in semantics on the other hand. Wher ..."
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Cited by 191 (16 self)
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In a series of papers, Petra Hendriks, Helen de Hoop, and Henriette de Swart Lave applied optimality theory (OT) to semantics. These authors argue that there is a fundamental difference between the form of OT as used in syntax on the one hand and its form as used in semantics on the other hand. Whereas in the first case OT takes the point of view of the speaker, in the second case the point of view of the hearer is taken. The aim of this paper is to argue that the proper treatment of OT in natural language interpretation has to take both perspectives at the same time. A conceptual framework is established that realizes the integration of both perspectives. It will be argued that this framework captures the essence of the Gricean maxims and gives a precise explication of Atlas & Levinson's (1981) idea of balancing between informativeness and efficiency in natural language processing. The ideas are then applied to resolve some puzzles in natural language interpretation. 1
Phonological acquisition in Optimality Theory: the early stages
, 2001
"... Recent experimental work indicates that by the age of ten months, infants have already learned a great deal about the phonotactics (legal sounds and sound sequences) of their language. This learning occurs before infants can utter words or apprehend most phonological alternations. I will show that t ..."
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Cited by 134 (6 self)
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Recent experimental work indicates that by the age of ten months, infants have already learned a great deal about the phonotactics (legal sounds and sound sequences) of their language. This learning occurs before infants can utter words or apprehend most phonological alternations. I will show that this early learning stage can be modeled with Optimality Theory. Specifically, the Markedness and Faithfulness constraints can be ranked so as to characterize the phonotactics, even when no information about morphology or phonological alternations is yet available. Later on, the information acquired in infancy can help the child in coming to grips with the alternation pattern. I also propose a procedure for undoing some learning errors that are likely to occur at the earliest stages. There are two formal proposals. One is a constraint ranking algorithm, based closely on Tesar and Smolensky’s Constraint Demotion, which mimics the early, “phonotactics only” form of learning seen in infants. I illustrate the algorithm’s effectiveness by having it learn the phonotactic pattern of a simplified language modeled on Korean. The other proposal is that there are three distinct default rankings for phonological constraints: low for ordinary Faithfulness (used in learning phonotactics); low for Faithfulness to adult forms (in the child’s own production system); and high for output-to-output correspondence constraints.
A Factorial Typology of Quantity-Insensitive Stress
- NATURAL LANGUAGE AND LINGUISTIC THEORY 20(3):491–552.'
, 2002
"... This paper presents an Optimality-theoretic (Prince and Smolensky 1993) analysis of quantity-insensitive stress. A set of grid-based constraints is shown by means of a computer-generated factorial typology to provide a relatively tight fit to the full range of stress systems attested in an extensive ..."
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Cited by 56 (0 self)
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This paper presents an Optimality-theoretic (Prince and Smolensky 1993) analysis of quantity-insensitive stress. A set of grid-based constraints is shown by means of a computer-generated factorial typology to provide a relatively tight fit to the full range of stress systems attested in an extensive survey of quantity-insensitive stress patterns, many of which have not been previously discussed in the theoretical literature.
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 50 (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
Against markedness (and what to replace it with)
, 2006
"... This paper first provides an overview of the various senses in which the terms "marked" and "unmarked" have been used in 20th century linguistics. Twelve different senses, related only by family resemblances, are distinguished, grouped into four larger classes: Markedness as comp ..."
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Cited by 49 (2 self)
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This paper first provides an overview of the various senses in which the terms "marked" and "unmarked" have been used in 20th century linguistics. Twelve different senses, related only by family resemblances, are distinguished, grouped into four larger classes: Markedness as complexity, as difficulty, as abnormality, and as a multidimensional correlation. In the second part of the paper, it is argued that the term "markedness" is superfluous, because some of the concepts that it denotes are not helpful, and others are better expressed by more straightforward, less ambiguous terms. In a great many cases, frequency asymmetries can be shown to lead to a direct explanation of observed structural asymmetries, and in other cases additional concrete, substantive factors such as phonetic difficulty and pragmatic inferences can replace references to an abstract notion of "markedness".
Convergence properties of a gradual learning algorithm for Harmonic Grammar
, 2008
"... This paper investigates a gradual on-line learning algorithm for Harmonic Grammar. By adapting existing convergence proofs for perceptrons, we show that for any nonvarying target language, Harmonic-Grammar learners are guaranteed to converge to an appropriate grammar, if they receive complete infor ..."
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Cited by 42 (15 self)
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This paper investigates a gradual on-line learning algorithm for Harmonic Grammar. By adapting existing convergence proofs for perceptrons, we show that for any nonvarying target language, Harmonic-Grammar learners are guaranteed to converge to an appropriate grammar, if they receive complete information about the structure of the learning data. We also prove convergence when the learner incorporates evaluation noise, as in Stochastic Optimality Theory. Computational tests of the algorithm show that it converges quickly. When learners receive incomplete information (e.g. some structure remains hidden), tests indicate that the algorithm is more likely to converge than two comparable Optimality-Theoretic learning algorithms.
Some Notes on the Formal Properties of Bidirectional Optimality Theory
"... In this paper, we discuss some formal properties of the model of bidirectional Optimality Theory that was developed in Blutner 2000. We investigate the conditions under which bidirectional optimization is a well-defined notion, and we give a conceptually simpler reformulation of Blutner's defin ..."
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Cited by 38 (2 self)
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In this paper, we discuss some formal properties of the model of bidirectional Optimality Theory that was developed in Blutner 2000. We investigate the conditions under which bidirectional optimization is a well-defined notion, and we give a conceptually simpler reformulation of Blutner's definition. In the second part of the paper, we show that bidirectional optimization can be modeled by means of finite state techniques. There we rely heavily on the related work of Frank and Satta 1998 about unidirectional optimization. 1 Introduction Optimality Theory (OT henceforth) has been introduced by Prince and Smolensky 1993 mainly as a model for generative Phonology, but in recent years this approach has been applied successfully to a range of syntactic phenomena, and it is currently gaining popularity in semantics and pragmatics as well. It rests on the old conception that the mapping from one level of linguistic representation to another level should be described in terms of transformatio...
Model theory and the content of OT constraints
- Phonology
, 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-outp ..."
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Cited by 30 (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. Background Optimality Theory (OT) constraints have developed a rich array of forms. The major families of constraint, markedness and faithfulness, each have identifiable subfamilies, differing, sometimes quite subtly, in their factual coverage, computational properties and implications for learnability. The result is a theory with intrinsic interest and impressive descriptive coverage. However, advocates of novel constraints have rarely been careful about exactly specifying the class of candidates necessary to achieve the intended interpretation. This lack of explicitness obscures a division among OT constraints. The present paper seeks to articulate this division by developing an extensible description language -a multimodal logic we call * We owe a huge thanks to an associate editor and four anonymous referees at Phonology, whose comments and insights substantially improved every aspect of this paper. Our thanks also to
