Functional segments in tongue movement

Stone, Maureen; Epstein, Melissa A.; Iskarous, Khalil

doi:10.1080/02699200410003583

Cited by 55 publications

(40 citation statements)

References 18 publications

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“…Each muscle bundle in tongue can be further divided into smaller functionally-distinct fibre groups, referred to as functional segments , which are believed to be controlled quasi-independently in a synergistic coordination (Stone et al 2004). We divide the vertical (GG, VRT) and horizontal (TRNS) muscle fibres into five functional segments (a: posterior to e: interior), as initially proposed by Miyawaki et al (1975) based on EMG measurements from GG, and later reinforced by Stone et al (2004) using ultrasound imaging and tagged-MRI information.…”

Section: Biomechanical Modelling Of Oropharynxmentioning

confidence: 99%

Subject-specific biomechanical modelling of the oropharynx: towards speech production

Harandi

Stavness

Woo

et al. 2015

Computer Methods in Biomechanics and Biomedical Engineering: Im

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Biomechanical models of the oropharynx are beneficial to treatment planning of speech impediments by providing valuable insight into the speech function such as motor control. In this paper, we develop a subject-specific model of the oropharynx and investigate its utility in speech production. Our approach adapts a generic tongue-jaw-hyoid model (Stavness et al. 2011) to fit and track dynamic volumetric MRI data of a normal speaker, subsequently coupled to a source-filter based acoustic synthesizer. We demonstrate our model’s ability to track tongue tissue motion, simulate plausible muscle activation patterns, as well as generate acoustic results that have comparable spectral features to the associated recorded audio. Finally, we propose a method to adjust the spatial resolution of our subject-specific tongue model to match the fidelity level of our MRI data and speech synthesizer. Our findings suggest that a higher resolution tongue model – using similar muscle fibre definition – does not show a significant improvement in acoustic performance, for our speech utterance and at this level of fidelity; however we believe that our approach enables further refinements of the muscle fibres suitable for studying longer speech sequences and finer muscle innervation using higher resolution dynamic data.

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Section: Biomechanical Modelling Of Oropharynxmentioning

confidence: 99%

Subject-specific biomechanical modelling of the oropharynx: towards speech production

Harandi

Stavness

Woo

et al. 2015

Computer Methods in Biomechanics and Biomedical Engineering: Im

Self Cite

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“…In the last two decades, researchers have shown a growing interest in ultrasound techniques. Ultrasound imaging has been used in many fields of linguistics and phonetics such as the interface between phonetics and phonology [1][2][3][4][5][6][7][8][9] , second language learning [10,11] , clinical phonetics [12][13][14][15] , speech development [16,17] and articulatory modeling [18] , among others. One of the advantages of this technique is that it provides a view of the global tongue con-tour in the midsagittal or coronal plane, whereas flesh-point tracking methods such as electromagnetic midsagittal articulography [19] or X-ray microbeam [20] provide coordinates of receivers attached to the tongue.…”

Section: Introductionmentioning

confidence: 99%

Measuring Tongue Shapes and Positions with Ultrasound Imaging: A Validation Experiment Using an Articulatory Model

Ménard

Aubin

Thibeault

et al. 2011

Folia Phoniatr Logop

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Objective: The goal of this paper is to assess the validity of various metrics developed to characterize tongue shapes and positions collected through ultrasound imaging in experimental setups where the probe is not constrained relative to the subject’s head. Patients and Methods: Midsagittal contours were generated using an articulatory-acoustic model of the vocal tract. Sections of the tongue were extracted to simulate ultrasound imaging. Various transformations were applied to the tongue contours in order to simulate ultrasound probe displacements: vertical displacement, horizontal displacement, and rotation. The proposed data analysis method reshapes tongue contours into triangles and then extracts measures of angles, x and y coordinates of the highest point of the tongue, curvature degree, and curvature position. Results: Parameters related to the absolute tongue position (tongue height and front/back position) are more sensitive to horizontal and vertical displacements of the probe, whereas parameters related to tongue curvature are less sensitive to such displacements. Conclusion: Because of their robustness to probe displacements, parameters related to tongue shape (especially curvature) are particularly well suited to cases where the transducer is not constrained relative to the head (studies with clinical populations or children).

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“…To investigate whether possible biomechanical constraints related to type of word pair and speaking rate contribute to possible differences in variability in movement patterns, correlations between movement range values of target and timesynchronous non-target articulators in word pairs with alternating and identical onsets were calculated. Correlations have been used in other studies to investigate biomechanical constraints between articulators (e.g., Green and Wang, 2003;Stone et al, 2004). Specifically, it is argued that if the correlation between movement range values of simultaneous target and non-target articulations is high, the articulators are not moving independently from one another due to biomechanical constraints.…”

Section: B Current Studymentioning

confidence: 98%

The effect of phonetic context on speech movements in repetitive speech

Slis

Lieshout

2013

The Journal of the Acoustical Society of America

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This study examined how, in repetitive speech, articulatory movements differ in degree of variability and movement range depending on articulatory constraints manipulated by phonetic context and type of CVC-CVC word pair. These pairs consisted of words that either differed in onset consonants but shared rhymes, or were identical. Articulatory constraints were manipulated by employing different combinations of vowels and consonants. The word pairs were produced in a repetitive speech task at a normal and fast speaking rate. Articulatory movements were measured with 3D electro-magnetic articulography. As measures of variability, median movement ranges and the coefficient of variation of target and non-target articulators were determined. To assess possible biomechanical constraints, correlation values between target and simultaneous non-target articulators were calculated as well. The results revealed that word pairs with different onsets had larger movement ranges than word pairs with identical onsets. In identical word pairs, the coefficient of variation showed higher values in the second than in the first word. This difference was not present in the alternating onset word pairs. For both types of word pairs, higher speaking rates showed higher correlations between target and non-target articulators than lower speaking rates, suggesting stronger biomechanical constraints for the former condition.

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Functional segments in tongue movement

Cited by 55 publications

References 18 publications

Subject-specific biomechanical modelling of the oropharynx: towards speech production

Subject-specific biomechanical modelling of the oropharynx: towards speech production

Measuring Tongue Shapes and Positions with Ultrasound Imaging: A Validation Experiment Using an Articulatory Model

The effect of phonetic context on speech movements in repetitive speech

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