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83
Optimal interleaving: serial phonologymorphology interaction in a constraintbased model
, 2008
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Harmonic grammar with linear programming: From linear . . .
, 2009
"... Harmonic Grammar (HG) is a model of linguistic constraint interaction in which wellformedness is calculated as the sum of weighted constraint violations. We show how linear programming algorithms can be used to determine whether there is a weighting for a set of constraints that fits a set of ling ..."
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Cited by 40 (9 self)
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Harmonic Grammar (HG) is a model of linguistic constraint interaction in which wellformedness is calculated as the sum of weighted constraint violations. We show how linear programming algorithms can be used to determine whether there is a weighting for a set of constraints that fits a set of linguistic data. The associated software package OTHelp provides a practical tool for studying large and complex linguistic systems in the HG framework and comparing the results with those of OT. We first describe the translation from Harmonic Grammars to systems solvable by linear programming algorithms. We then develop an HG analysis of ATR harmony in Lango that is, we argue, superior to the existing OT and rulebased treatments. We further highlight the usefulness of OTHelp, and the analytic power of HG, with a set of studies of the predictions HG makes for phonological typology.
Weighted Constraints in Generative Linguistics
 Cognitive Science
, 2009
"... Harmonic Grammar (HG) and Optimality Theory (OT) are closely related formal frameworks for the study of language. In both, the structure of a given language is determined by the relative strengths of a set of constraints. They differ in how these strengths are represented: as numerical weights (HG) ..."
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Cited by 21 (3 self)
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Harmonic Grammar (HG) and Optimality Theory (OT) are closely related formal frameworks for the study of language. In both, the structure of a given language is determined by the relative strengths of a set of constraints. They differ in how these strengths are represented: as numerical weights (HG) or as ranks (OT). Weighted constraints have advantages for the construction of accounts of language learning and other cognitive processes, partly because they allow for the adaptation of connectionist and statistical models. HG has been little studied in generative linguistics, however, largely due to influential claims that weighted constraints make incorrect predictions about the typology of natural languages, predictions that are not shared by the more popular OT. This paper makes the case that HG is in fact a promising framework for typological research, and reviews and extends the existing arguments for weighted over ranked constraints. 1
The serial interaction of stress and syncope
"... Many languages respect the generalization that some or all unstressed vowels are deleted. This generalization proves elusive in classic Optimality Theory, however. The source of the problem is classic OT’s parallel evaluation, which requires that the effects of stress assignment and syncope be optim ..."
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Cited by 20 (8 self)
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Many languages respect the generalization that some or all unstressed vowels are deleted. This generalization proves elusive in classic Optimality Theory, however. The source of the problem is classic OT’s parallel evaluation, which requires that the effects of stress assignment and syncope be optimized together. This article argues for a version of OT called Harmonic Serialism, in which the effects of stress assignment and syncope can and must be evaluated sequentially. The results are potentially applicable to other domains where process interaction is best understood in derivational terms.
The winner takes it all  almost. cumulativity in grammatical variation. Linguistics
, 2006
"... Classical Optimality Theory in the sense of Prince and Smolensky (2004/1993) implements the intuition that grammars cannot count. The grammaticality of a candidate is fully determined by the ranking of the relevant constraints. Numerical constraint weights play no role. Furthermore, if a competition ..."
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Cited by 19 (0 self)
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Classical Optimality Theory in the sense of Prince and Smolensky (2004/1993) implements the intuition that grammars cannot count. The grammaticality of a candidate is fully determined by the ranking of the relevant constraints. Numerical constraint weights play no role. Furthermore, if a competition between two candidates is decided by a constraint c, it
Iterative foot optimization and locality in stress systems. Ms
, 2008
"... Abstract. This paper proposes a model of stress assignment in which metrical structure is built serially – one foot at a time – through a series of OTstyle evaluations. Iterative foot optimization (IFO) is made possible in the framework of Harmonic Serialism, which defines the path from an input to ..."
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Cited by 19 (1 self)
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Abstract. This paper proposes a model of stress assignment in which metrical structure is built serially – one foot at a time – through a series of OTstyle evaluations. Iterative foot optimization (IFO) is made possible in the framework of Harmonic Serialism, which defines the path from an input to an output with a series of gradual changes in which each form is more harmonic than its predecessor, relative to a constraint ranking. Stress assignment in IFO is compared to parallel OT and it is found that they predict different classes of languages even when the same standard stress constraints are considered. IFO makes the strong prediction that decisions about metrical structure are made locally, while parallel OT predicts stress systems with nonlocal interactions. The interactions of stress with syllable weight, vowel shortening, and edge restrictions are considered, and in all cases it is shown that attested languages exhibit local interactions, while parallel OT predicts nonlocal counterparts which are not clearly attested. 1
Linguistic optimization
"... Optimality Theory (OT) is a model of language that combines aspects of generative and connectionist linguistics. It is unique in the field in its use of a rank ordering on constraints, which is used to formalize optimization, the choice of the best of a set of potential linguistic forms. We show tha ..."
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Cited by 16 (2 self)
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Optimality Theory (OT) is a model of language that combines aspects of generative and connectionist linguistics. It is unique in the field in its use of a rank ordering on constraints, which is used to formalize optimization, the choice of the best of a set of potential linguistic forms. We show that phenomena argued to require ranking fall out equally from the form of optimization in OT’s predecessor Harmonic Grammar (HG), which uses numerical weights to encode the relative strength of constraints. We further argue that the known problems for HG can be resolved by adopting assumptions about the nature of constraints that have precedents both in OT and elsewhere in computational and generative linguistics. This leads to a formal proof that if the range of each constraint is a bounded number of violations, HG generates a finite number of languages. This is nontrivial, since the set of possible weights for each constraint is nondenumerably infinite. We also briefly review some advantages of HG. 1
Serial Harmonic Grammar and Berber Syllabification *
"... version of OT in which the representation is changed ..."
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Cited by 10 (2 self)
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version of OT in which the representation is changed
Locality in metrical typology
, 2009
"... Recent work in metrical typology within Optimality Theory has emphasised the rhythmic distribution of stress peaks by reference to clashes and lapses, compared to the more central role of foot constituency characteristic of most previous approaches. One consequence of this emphasis has been the intr ..."
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Cited by 10 (4 self)
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Recent work in metrical typology within Optimality Theory has emphasised the rhythmic distribution of stress peaks by reference to clashes and lapses, compared to the more central role of foot constituency characteristic of most previous approaches. One consequence of this emphasis has been the introduction of constraints that require reference to nonadjacent objects in the representation, such as two unstressed syllables plus a word edge or a stress peak. I argue here for a constraintbased approach to metrical typology that permits only strictly local formulations. This approach requires increased reference to foot structure, while maintaining local reference to clashes and lapses. The revised set of constraints predicts a larger set of possible stress systems, but correctly includes an attested iambic pattern excluded by recent theories.
On the Role of Locality in Learning Stress Patterns
, 2008
"... This paper presents a previously unnoticed universal property of stress patterns in the world’s languages: they are, for small neighborhoods, neighborhooddistinct. Neighborhooddistinctness is a locality condition defined in automatatheoretic terms. This universal is established by examining stres ..."
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Cited by 8 (4 self)
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This paper presents a previously unnoticed universal property of stress patterns in the world’s languages: they are, for small neighborhoods, neighborhooddistinct. Neighborhooddistinctness is a locality condition defined in automatatheoretic terms. This universal is established by examining stress patterns contained in two typological studies, Bailey (1995) and Gordon (2002). Strikingly, many logically possible— but unattested—patterns do not have this property. Not only does neighborhooddistinctness unite the attested patterns in a nontrivial way, it also naturally provides an inductive principle allowing learners to generalise from limited data. A learning algorithm is presented which generalises by failing to distinguish sameneighborhood environments perceived in the learner’s linguistic input—hence learning neighborhooddistinct patterns—as well as almost every stress pattern in the typology. In this way, this work lends support to the idea that properties of the learner can explain certain properties of the attested typology, an idea not straightforwardly available in Optimalitytheoretic and Principle and Parameter frameworks.