Inter- and intra- speaker variance in sound changeJosef Fruehwald

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Speech Community and Speaker Heterogeneity

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Convergence Model of Sound ChangeOne model of the actuation & progression of sound change involvesconvergence either across or within speakers on a new norm.

S-retraction & /r/ heterogeneity in North American English (Baker,Archangeli & Mielke, 2011; Mielke, Baker & Archangeli, 2016)The Synchronic Pool of Variation (Ohala, 1989)CHOICE Blevins (2004)

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Convergence Model of Sound Change

Inter- or intra speaker variance decreases over time.

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Convergence Model of Sound ChangeIn the study of sound change in progress, we almost exclusively focus on thelocation parameters of our community & speaker distributions, but hardlyever the scale parameters .

In this talk

Examining in two changes and two non-changes from the PhiladelphiaNeighborhood corpus

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Philadelphia Neighborhood Corpus325 Speakers from PhiladelphiaInterviewed between 1973 and 2013Dates of birth from 1889 and 1998Force-aligned and formants automatically estimated with the FAVE-suite

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ModellingBayesian modelling via Hamiltonian Monte Carlo

Implemented in Stan

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Changes Examined - /ay/ allphones

84,746 tokens

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Changes Examined - /ey/ allphones

46,152 tokens

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Intra-speaker variance model

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DescriptionLocation autoregression model

δiμi

δi+1μi+1 = μi + δi

μi+2 = μi+1 + δi+1

δi ~ normal(δi-1, σ)

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DescriptionScale autoregression model

σi

σi+1 = σi × eδi

σi+2 = σi+1 × eδi+1

δi ~ normal(δi-1, σ)

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DescriptionIntra-speaker variance model

AR Process

half-cauchy

μ

normal

σ

μ

normal

σ

AR Process

hyperpriors

priors

speaker-leveldistributions

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Results

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Results

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Results

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ConclusionThe degree of intra-speaker variance remained remarkably consistent acrossthe 20th century

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Inter-speaker variance model

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Description

AR Process

μ

normal

σ

AR Processhyperpriors

priors

speaker-leveldistributions

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Results

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Results

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Results

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ConclusionThe degree of inter-speaker differences has also remained remarkablyconsistent across the 20th century.

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Discussion

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Resulting Picture

time

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GapsTo explore in the future:

Greater exploration of the by-speaker estimates

Outlier speakers/tokens (Labov et al 2010)

t or cauchy distributions?

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The End

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