A Canonical Semi-Deterministic Transducer

Beros, Achilles A.; Higuera, Colin de la

doi:10.3233/fi-2016-1394

Cited by 5 publications

(3 citation statements)

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“… 11 Cases of free variation are thus not maps, as one UR can be paired with multiple SRs. The focus of the present study is on subclasses of maps, and so such cases will not be considered, but (finite) free variation can be studies in a similar way with the p-subsequential transducers of Mohri (1997) or the semi-deterministic transducers of Beros & de la Higuera (2014). …”

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confidence: 99%

Computationally, tone is different

Jardine

2016

Phonology

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This paper establishes that unbounded circumambient processes, phonological processes for which crucial information in the environment may appear unboundedly far away on both sides of a target, are common in tonal phonology, but rare in segmental phonology. It then argues that this typological asymmetry is best characterised by positing that tone is more computationally complex than segmental phonology. The evidence for the asymmetry is based around attestations of unbounded tonal plateauing, but it is also shown how the 'sour-grapes' harmony pathology is unbounded circumambient. The paper argues that such processes are not weakly deterministic, which contrasts with previous typological work on segmental phonology. Positing that weak determinism bounds segmental phonology but not tonal phonology thus captures the typological asymmetry. It is also discussed why this explanation is superior to any offered by Optimality Theory.

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confidence: 99%

Computationally, tone is different

Jardine

2016

Phonology

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“…Finally, we are also interested in extending these results to weighted deterministic automata for computing regular relations (Beros and de la Higuera, 2016) or elements of other monoids (Gerdjikov, 2018).…”

Section: Discussionmentioning

confidence: 99%

Maximum Likelihood Estimation of Factored Regular Deterministic Stochastic Languages

Shibata

Heinz

2019

Proceedings of the 16th Meeting on the Mathematics of Language

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This paper proves that for every class C of stochastic languages defined with the coemission product of finitely many probabilistic, deterministic finite-state acceptors (PDFA) and for every data sequence D of finitely many strings drawn i.i.d. from some stochastic language, the Maximum Likelihood Estimate of D with respect to C can be found efficiently by locally optimizing the parameter values. We show that a consequence of the co-emission product is that each PDFA behaves like an independent factor in a joint distribution. Thus, the likelihood function decomposes in a natural way. We also show that the negative log likelihood function is convex. These results are motivated by the study of Strictly k-Piecewise (SP k) Stochastic Languages, which form a class of stochastic languages which is both linguistically motivated and naturally understood in terms of the coemission product of certain PDFAs.

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“…(Mohri, 1997) establishes that as long as there is a bound on the amount of optionality, that many properties of subsequential functions are preserved. More recently, Beros and de la Higuera (2014) also show how to generalize subsequential functions in a way that permits a degree of optionality. While subclasses of classes have not been studied the fact that they preserve important aspects of the underlying finite-state transducers and that classes like ISL have automata-theoretic characterizations based on subsequential transducers (Chandlee, 2014;Chandlee et al, 2014a) strongly suggests that subclasses like ISL which permit a degree of optionality are only waiting to be discovered.…”

Section: Non-deterministic Regular Functions and Regular Relationsmentioning

confidence: 99%

The computational nature of phonological generalizations

Heinz¹

2018

Phonological Typology

108

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This chapter studies the nature of the typology of phonological markedness constraints and the nature of the typology of the transformation from underlying to surface forms from a computational perspective. It argues that there are strong computational laws that constrain the form of these constraints and transformations. These laws are currently stated most clearly in terms of the so-called subregular hierarchies, which have been established for stringsets (for modeling constraints) and are currently being established for string-to-string maps (for modeling the transformations). It is anticipated that future research will reveal equally powerful laws applicable to non-string-based representations. Finally, this chapter argues that these laws arise as a natural consequence of how humans generalize from data.Wilhelm von Humboldt's phrase "language makes infinite use of finite means" (1836/1999) is oft-cited by Chomsky because not only does it encapsulate an important characteristic of natural language, but it also highlights why generative grammars play an important role in understanding this aspect of language. In brief, the generative grammars are the finite means, but the linguistic knowledge they represent can be applied to unboundedly many linguistic forms. The psychological reality of generative grammars is the powerful scientific hypothesis which underlies all work in generative linguistics.

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A Canonical Semi-Deterministic Transducer

Cited by 5 publications

References 41 publications

Computationally, tone is different

Computationally, tone is different

Maximum Likelihood Estimation of Factored Regular Deterministic Stochastic Languages

The computational nature of phonological generalizations

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