Inter-speaker articulatory variability during vowel-consonant-vowel sequences in twins and unrelated speakers

Weirich, Melanie; Lancia, Leonardo; Brunner, Jana

doi:10.1121/1.4822480

Cited by 12 publications

(6 citation statements)

References 51 publications

(70 reference statements)

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“…The number of swallows (Rudney et al, 1995) and of words produced per day (Mehl et al, 2007) varies considerably between individuals. Moreover, the biomechanics of articulation (Weirich et al, 2013) and of swallowing (Kennedy et al, 2010) is characterized by substantial inter-individual variability. To investigate individual brain activity, we performed an independent component analysis (ICA) of individual taskbased FMRI data sets.…”

Section: Introductionmentioning

confidence: 99%

Model-Based and Model-Free Analyses of the Neural Correlates of Tongue Movements

2020

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The tongue performs movements in all directions to subserve its diverse functions in chewing, swallowing, and speech production. Using task-based functional MRI in a group of 17 healthy young participants, we studied (1) potential differences in the cerebral control of frontal (protrusion), horizontal (side to side), and vertical (elevation) tongue movements and (2) inter-individual differences in tongue motor control. To investigate differences between different tongue movements, we performed voxel-wise multiple linear regressions. To investigate inter-individual differences, we applied a novel approach, spatio-temporal filtering of independent components. For this approach, individual functional data were decomposed into spatially independent components and corresponding time courses using independent component analysis. A temporal filter (correlation with the expected brain response) was used to identify independent components time-locked to the tongue motor tasks. A spatial filter (cross-correlation with established neurofunctional systems) was used to identify brain activity not timelocked to the tasks. Our results confirm the importance of an extended bilateral cortical and subcortical network for the control of tongue movements. Frontal (protrusion) tongue movements, highly overlearned movements related to speech production, showed less activity in the frontal and parietal lobes compared to horizontal (side to side) and vertical (elevation) movements and greater activity in the left frontal and temporal lobes compared to vertical movements (cluster-forming threshold of Z > 3.1, cluster significance threshold of p < 0.01, corrected for multiple comparisons). The investigation of inter-individual differences revealed a component representing the tongue primary sensorimotor cortex time-locked to the task in all participants. Using the spatial filter, we found the default mode network in 16 of 17 participants, the left fronto-parietal network in 16, the right fronto-parietal network in 8, and the executive control network in four participants (Pearson's r > 0.4 between neurofunctional systems and individual components). These results demonstrate that spatio-temporal filtering of independent components allows to identify individual brain activity related to a specific task and also structured spatiotemporal processes representing known neurofunctional systems on an individual basis. This novel approach may be useful for the assessment of individual patients and results may be related to individual clinical, behavioral, and genetic information.

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Section: Introductionmentioning

confidence: 99%

Model-Based and Model-Free Analyses of the Neural Correlates of Tongue Movements

2020

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“…The fact that part of inter-individual variability is indeed free rather than constrained by the physical, biological, linguistic or sociocultural environment is best evidenced by studies of speech produced by members of the same family. A number of studies have been published concerning monozygotic or dizygotic twin pairs, providing both similarities and differences in vocal tract and vocal source characteristics [36–38]. In a recent study on vowel production in 10 pairs of French adult male siblings, [39] showed that the inter-individual acoustic variability was globally lower between brothers, compared with speakers that were not brothers.…”

Section: Introductionmentioning

confidence: 99%

Computer simulations of coupled idiosyncrasies in speech perception and speech production with COSMO, a perceptuo-motor Bayesian model of speech communication

Barnaud

Schwartz

Bessìère³

et al. 2019

PLoS ONE

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The existence of a functional relationship between speech perception and production systems is now widely accepted, but the exact nature and role of this relationship remains quite unclear. The existence of idiosyncrasies in production and in perception sheds interesting light on the nature of the link. Indeed, a number of studies explore inter-individual variability in auditory and motor prototypes within a given language, and provide evidence for a link between both sets. In this paper, we attempt to simulate one study on coupled idiosyncrasies in the perception and production of French oral vowels, within COSMO, a Bayesian computational model of speech communication. First, we show that if the learning process in COSMO includes a communicative mechanism between a Learning Agent and a Master Agent, vowel production does display idiosyncrasies. Second, we implement within COSMO three models for speech perception that are, respectively, auditory, motor and perceptuo-motor. We show that no idiosyncrasy in perception can be obtained in the auditory model, since it is optimally tuned to the learning environment, which does not include the motor variability of the Learning Agent. On the contrary, motor and perceptuo-motor models provide perception idiosyncrasies correlated with idiosyncrasies in production. We draw conclusions about the role and importance of motor processes in speech perception, and propose a perceptuo-motor model in which auditory processing would enable optimal processing of learned sounds and motor processing would be helpful in unlearned adverse conditions.

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“…However, numerous studies have revealed the existence of inter-speaker articulatory variability related to morphological differences between speakers and idiosyncratic articulatory strategies ( [5], [6]). It has been demonstrated that the inter-speaker variability partly corresponds to an adaptation to the morphology ( [7][8][9][10][11][12][13]). Other studies have also emphasised the relationships between speaker's strategy and morphology by means of articulatory normalisation ( [14], [15]), multi-speaker modelling aiming to uncover the common articulatory features ( [5], [16][17][18][19][20][21][22][23][24][25]), or sensitivity analysis of area function models [26].…”

Section: Introductionmentioning

confidence: 99%

Inter-Speaker Variability: Speaker Normalisation and Quantitative Estimation of Articulatory Invariants in Speech Production for French

Serrurier¹,

Badin²,

Boë³

et al. 2017

Interspeech 2017

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Speech production can be analysed in terms of universal articulatory-acoustic phonemic units shared between speakers. However, morphological differences between speakers and idiosyncratic articulatory strategies lead to large inter-speaker articulatory variability. Relationships between strategy and morphology have already been pinpointed in the literature. This study aims thus at generalising existing results on a larger database for the entire vocal tract (VT) and at quantifying phoneme-specific inter-speaker articulatory invariants. Midsagittal MRI of 11 French speakers for 62 vowels and consonants were recorded and VT contours manually edited. A procedure of normalisation of VT contours between speakers, based on the use of mean VT contours, led to an overall reduction of inter-speaker VT contours variance of 88%. On the opposite, the sagittal function (i.e. the transverse sagittal distance along the VT midline), which is the main determinant of the acoustic output, had an overall amplitude variance decrease of only 37%, suggesting that the speakers adapt their strategy to their morphology to achieve proper acoustic goals. Moreover, articulatory invariants were identified on the sagittal variance distribution along the VT as the regions with lower variability. These regions correspond to the classical places of articulation and are associated with higher acoustic sensitivity function levels.

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Inter-speaker articulatory variability during vowel-consonant-vowel sequences in twins and unrelated speakers

Cited by 12 publications

References 51 publications

Model-Based and Model-Free Analyses of the Neural Correlates of Tongue Movements

Model-Based and Model-Free Analyses of the Neural Correlates of Tongue Movements

Computer simulations of coupled idiosyncrasies in speech perception and speech production with COSMO, a perceptuo-motor Bayesian model of speech communication

Inter-Speaker Variability: Speaker Normalisation and Quantitative Estimation of Articulatory Invariants in Speech Production for French

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