2017
DOI: 10.3765/amp.v4i0.3997
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Varieties of Noisy Harmonic Grammar

Abstract: Background: Stochastic constraint-based grammar frameworks in modern linguisticsThe key innovation of Optimality Theory (Prince and Smolensky 1993) was its GEN-plus-EVAL architecture: GEN enumerates candidates, and EVAL, consisting of a set of constraints, selects the winning candidate from GEN as the output. This conception naturally led to the idea of a stochastic version of the theory, in which EVAL outputs not one single candidate but rather a probability distribution over GEN. Such a framework would provi… Show more

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Cited by 22 publications
(19 citation statements)
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“…The field of phonology has recently witnessed a rise of interest in formal grammatical models which can account for such stochastic phonological generalisations. Among these, the three most widely employed frameworks are (i) Stochastic Optimality Theory (Boersma 1998, Boersma & Hayes 2001, (ii) Noisy Harmonic Grammar (Coetzee & Kawahara 2013, Boersma & Pater 2016, Hayes 2017 and (iii) Maximum Entropy Harmonic Grammar (henceforth MaxEnt) (Goldwater & Johnson 2003, Zuraw & Hayes 2017. How these stochastic models of phonology should be teased apart is currently a topic of debate in phonological studies (Jäger & Rosenbach 2006, Jäger 2007, Hayes 2017, Zuraw & Hayes 2017, Anttila & Magri 2018, Breiss 2020, among many others).…”
Section: A Wug-shaped Curvementioning
confidence: 99%
“…The field of phonology has recently witnessed a rise of interest in formal grammatical models which can account for such stochastic phonological generalisations. Among these, the three most widely employed frameworks are (i) Stochastic Optimality Theory (Boersma 1998, Boersma & Hayes 2001, (ii) Noisy Harmonic Grammar (Coetzee & Kawahara 2013, Boersma & Pater 2016, Hayes 2017 and (iii) Maximum Entropy Harmonic Grammar (henceforth MaxEnt) (Goldwater & Johnson 2003, Zuraw & Hayes 2017. How these stochastic models of phonology should be teased apart is currently a topic of debate in phonological studies (Jäger & Rosenbach 2006, Jäger 2007, Hayes 2017, Zuraw & Hayes 2017, Anttila & Magri 2018, Breiss 2020, among many others).…”
Section: A Wug-shaped Curvementioning
confidence: 99%
“…We opt for the more established Maximum Entropy framework (MaxEnt;Goldwater & Johnson 2003, Wilson 2006. For a broader review of gradient constraint-based approaches, see Hayes (2017).…”
Section: Protection Of Existing Itemsmentioning
confidence: 99%
“…For completeness, (45) shows how the weights can be adjusted to produce Eastern Andalusian's indirect-licensing variants by adopting weights conforming to (35a). For discussion of manipulating weights to produce variation in HG, see Jesney (2007), Pater et al (2007) and Hayes (2017). I leave it for future work to flesh out a rigorous analysis of this optionality (for example, with the reduction in IDENT's weight, the weight of *ɪ,ʊ must be increased to retain the result in (44)), but this gives an indication of what such an analysis might look like.…”
Section: Eastern Andalusian the Salient Difference Between The Licenmentioning
confidence: 99%