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Characterization of inter-speaker articulatory variability: A two-level multi-speaker modelling approach based on MRI data

Abstract : Speech communication relies on articulatory and acoustic codes shared between speakers and listeners despite inter-individual differences in morphology and idiosyncratic articulatory strategies. This study addresses the long-standing problem of characterizing and modelling speaker-independent articulatory strategies and inter-speaker articulatory variability. It explores a multi-speaker modelling approach based on two levels: statistically-based linear articulatory models, which capture the speakerspecific articulatory variability on the one hand, are in turn controlled by a speaker model, which captures the inter-speaker variability on the other hand. A low dimensionality speaker model is obtained by taking advantage of the inter-speaker correlations between morphology and strategy. To validate this approach, contours of the vocal tract articulators were manually segmented on midsagittal MRI data recorded from 11 French speakers uttering 62 vowels and consonants. Using these contours, multi-speaker models with 14 articulatory components and two morphology and strategy components led to overall variance explanations of 66%–69% and root-mean-square errors of 0.36–0.38 cm obtained in leave-one-out procedure over the speakers. Results suggest that inter-speaker variability is more related to the morphology than to the idiosyncratic strategies and illustrate the adaptation of the articulatory components to the morphology.
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https://hal.archives-ouvertes.fr/hal-02106595
Contributor : Pierre Badin Connect in order to contact the contributor
Submitted on : Thursday, November 26, 2020 - 8:12:25 PM
Last modification on : Wednesday, November 3, 2021 - 5:09:51 AM
Long-term archiving on: : Saturday, February 27, 2021 - 6:03:41 PM

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Antoine Serrurier, Pierre Badin, Laurent Lamalle, Christiane Neuschaefer-Rube. Characterization of inter-speaker articulatory variability: A two-level multi-speaker modelling approach based on MRI data. Journal of the Acoustical Society of America, Acoustical Society of America, 2019, 145 (4), pp.2149-2170. ⟨10.1121/1.5096631⟩. ⟨hal-02106595⟩

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