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Linglib.Phenomena.Phonotactics.Studies.HayesWilson2008

@cite{hayes-wilson-2008}: A Maximum Entropy Model of Phonotactics #

@cite{hayes-wilson-2008}

@cite{hayes-wilson-2008} propose that phonotactic well-formedness is probability: a MaxEnt grammar assigns each surface form a score h(x) = Σ wⱼ · Cⱼ(x), and well-formedness is P(x) = exp(−h(x)) / Z.

Hayes & Wilson's "score" is the negation of harmonyScore: h(x) = −harmonyScore(x), so P(x) ∝ exp(harmonyScore(x)). Higher harmony = higher probability = better well-formedness. This is exactly softmax(harmonyScoreR, 1) on a finite candidate set.

Key contribution: ganging #

The central empirical prediction distinguishing MaxEnt from OT is ganging: two individually weak constraints can jointly override a stronger one. This is impossible with OT's strict ranking, which corresponds to exponentially separated weights (OTLimit.lean).

The Ganging definition and anti-ganging theorems live in OTLimit.lean alongside ExponentiallySeparated, since they are two sides of the same coin.

English onset data #

We encode a subset of the learned grammar (Table (4)) and verify that the model assigns higher harmony (= higher MaxEnt probability via exp_lt_exp) to attested onsets than to unattested ones (§2).

@[reducible, inline]

An English onset: a list of consonants preceding the nucleus.

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    Constraint #1 from Table (4): *[+sonorant, +dorsal]. Weight 5.64.

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      Constraint #4 from Table (4): *[ ][+continuant]. Weight 5.17.

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        Constraint #5 from Table (4): *[ ][+voice, −sonorant]. Weight 5.37.

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          Constraint #6 from Table (4): *[+sonorant][ ]. Weight 6.66.

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            The subset grammar: 4 constraints from Table (4).

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              MaxEnt probability ordering: higher harmony ⟹ higher exp(harmonyScore) ⟹ higher MaxEnt probability.

              Applies exp_lt_exp (Mathlib) to harmonyScoreR (HarmonicGrammar.Basic).