Literature DB >> 31046321

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

Antoine Serrurier1, Pierre Badin2, Laurent Lamalle3, Christiane Neuschaefer-Rube1.   

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 speaker-specific 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.

Year:  2019        PMID: 31046321     DOI: 10.1121/1.5096631

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  3 in total

Review 1.  Computer-Implemented Articulatory Models for Speech Production: A Review.

Authors:  Bernd J Kröger
Journal:  Front Robot AI       Date:  2022-03-08

2.  Automatic vocal tract landmark localization from midsagittal MRI data.

Authors:  Mohammad Eslami; Christiane Neuschaefer-Rube; Antoine Serrurier
Journal:  Sci Rep       Date:  2020-01-30       Impact factor: 4.379

3.  Printable 3D vocal tract shapes from MRI data and their acoustic and aerodynamic properties.

Authors:  Peter Birkholz; Steffen Kürbis; Simon Stone; Patrick Häsner; Rémi Blandin; Mario Fleischer
Journal:  Sci Data       Date:  2020-08-05       Impact factor: 6.444

  3 in total

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