, Les organisations de la société civile rapportent que des consultations ne sont pas systématiquement utilisées pour orienter les politiques nationales de développement, une articulation stable est un défi pour l'orateur. Cependant, dans les Dans le cas des voyelles, la situation est meilleure puisque les voyelles peuvent être prononcées seules, 2019.

, Vers un modèle psycholinguistique du locuteur, Textes pour une psycholinguistique, pp.7-22, 1974.

C. Dans-ce, Une autre contribution est l'utilisation de la technique du kernel gaussien adaptatif pour créer les échantillons de l'atlas avec l'avantage de rendre la fréquence de trame de l'atlas indépendante de la fréquence de trame de l'IRMtr. La méthode proposée donne donc plus de souplesse pour contrôler l'atlas résultant paramètres. Les mêmes données peuvent donc être utilisées pour créer divers atlas avec des paramètres différents sans qu'il soit nécessaire de procéder à de nouvelles acquisitions de données à chaque fois. Enfin, et c'est un avantage déterminant dans l'étude de la production de la parole, l'atlas construit avec cette méthode peut être utilisé comme locuteur de référence pour réduire la variabilité entre et au sein des sujets. En effet, de nombreux travaux consacrés à la production de la parole d'un point de vue général sont basés sur l'hypothèse implicite d'un modèle articulatoire construit à partir d'un seul locuteur, ce qui est le cas du célèbre modèle articulatoire de Maeda, est valable pour tous les locuteurs. Il s'agit d'une simplification qui réduit la portée et la validité Bibliography, nous proposons une méthode que l'on peut utiliser pour créer un locuteur artificiel qui peut être utilisé comme locuteur standard. Cela permettra à quelqu'un non seulement de trouver des solutions potentiellement meilleures à des problèmes partiellement résolus/explorés mais aussi pour étudier les questions sous un angle nouveau, vol.140, pp.1707-1718, 2016.

M. Ahmad, J. Dargaud, A. Morin, and F. Cotton, Dynamic MRI of Larynx and Vocal Fold Vibrations in Normal Phonation, Journal of Voice, vol.23, issue.2, pp.235-239, 2009.

S. Abeer-alwan, K. Narayanan, and . Haker, Toward articulatory-acoustic models for liquid approximants based on mri and epg data. part ii. the rhotics, The Journal of the Acoustical Society of America, vol.101, issue.2, pp.1078-1089, 1997.

N. Agarwal, X. Xu, and M. Gopi, Robust registration of Mouse brain slices with severe histological artifacts, Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing - ICVGIP '16, p.10, 2016.

D. Beautemps, P. Badin, and G. Bailly, Linear degrees of freedom in speech production: Analysis of cineradio- and labio-film data and articulatory-acoustic modeling, The Journal of the Acoustical Society of America, vol.109, issue.5, pp.2165-2180, 2001.

P. Badin, G. Bailly, L. Revéret, M. Baciu, C. Segebarth et al., Three-dimensional linear articulatory modeling of tongue, lips and face, based on MRI and video images, Journal of Phonetics, vol.30, issue.3, pp.533-553, 2002.
URL : https://hal.archives-ouvertes.fr/hal-00798689

P. Badin, G. Bailly, L. Revéret, M. Baciu, C. Segebarth et al., Three-dimensional linear articulatory modeling of tongue, lips and face, based on MRI and video images, Journal of Phonetics, vol.30, issue.3, pp.533-553, 2002.
URL : https://hal.archives-ouvertes.fr/hal-00798689

T. Baer, J. C. Gore, L. C. Gracco, and P. W. Nye, Analysis of vocal tract shape and dimensions using magnetic resonance imaging: Vowels, The Journal of the Acoustical Society of America, vol.90, issue.2, pp.799-828, 1991.

P. Birkholz, Articulatory synthesis of singing. In Eighth Annual Conference of the International Speech Communication Association, 2007.

P. Birkholz, Modeling Consonant-Vowel Coarticulation for Articulatory Speech Synthesis, PLoS ONE, vol.8, issue.4, p.e60603, 2013.

P. Birkholz, D. Jackel, and B. J. Kroger, Construction And Control Of A Three-Dimensional Vocal Tract Model, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, vol.1

E. Bresch, A. Katsamanis, L. Goldstein, S. Shrikanth, and . Narayanan, Statistical multi-stream modeling of real-time mri articulatory speech data, Eleventh Annual Conference of the International Speech Communication Association, 2010.

E. Bresch, J. Nielsen, K. Nayak, and S. Narayanan, Synchronized and noise-robust audio recordings during realtime magnetic resonance imaging scans, The Journal of the Acoustical Society of America, vol.120, issue.4, pp.1791-1794, 2006.

P. Badin, M. Tabain, and L. Lamalle, Comparative study of coarticulation in a multilingual speaker: Preliminary results from mri data, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02279473

P. Birkholz and E. Venus, Considering Lip Geometry in One-Dimensional Tube Models of the Vocal Tract, Studies on Speech Production, pp.78-86, 2018.

P. Boersma and D. Weenink, Praat, a system for doing phonetics by computer, Glot International, vol.5, issue.9, pp.341-345, 2001.

E. Calabrese, A. Badea, C. Watson, and G. A. Johnson, A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability, NeuroImage, vol.71, pp.196-206, 2013.

N. Chauffert, P. Ciuciu, and P. Weiss, Variable density compressed sensing in MRI. Theoretical vs heuristic sampling strategies, 2013 IEEE 10th International Symposium on Biomedical Imaging, pp.298-301, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00848271

C. Carignan, P. Hoole, E. Kunay, M. Pouplier, A. Joseph et al., Analyzing speech in both time and space: Generalized additive mixed models can uncover systematic patterns of variation in vocal tract shape in real-time MRI, Laboratory Phonology: Journal of the Association for Laboratory Phonology, vol.11, issue.1, pp.413-417, 2020.

V. Caselles, R. Kimmel, G. Sapiro-;-nelson-chuang, S. Mori, A. Yamamoto et al., An mri-based atlas and database of the developing mouse brain, International journal of computer vision, vol.22, issue.1, pp.80-89, 1997.

F. Charpentier and M. Stella, Diphone synthesis using an overlap-add technique for speech waveforms concatenation, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol.11, pp.2015-2018

C. Carignan, R. K. Shosted, M. Fu, Z. Liang, and B. P. Sutton, A real-time MRI investigation of the role of lingual and pharyngeal articulation in the production of the nasal vowel system of French, Journal of Phonetics, vol.50, pp.34-51, 2015.

B. Boer, Investigating the acoustic effect of the descended larynx with articulatory models, Journal of Phonetics, vol.38, issue.4, pp.679-686, 2010.

C. Brad, T. Davis, E. Fletcher, S. Bullitt, and . Joshi, Population shape regression from random design data. International journal of computer vision, vol.90, pp.255-266, 2010.

D. Demolin, S. Hassid, T. Metens, and A. Soquet, Real-time MRI and articulatory coordination in speech, Comptes Rendus Biologies, vol.325, issue.4, pp.547-556, 2002.

A. Ioannis-k-douros, P. Katsamanis, and . Maragos, Multiview audio-articulatory features for phonetic recognition on rtmri-timit database, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5514-5518, 2018.

I. K. Douros, J. Felblinger, J. Frahm, K. Isaieva, A. A. Joseph et al., A Multimodal Real-Time MRI Articulatory Corpus of French for Speech Research, Interspeech 2019, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02167756

I. K. Douros, A. Tsukanova, K. Isaieva, P. Vuissoz, and Y. Laprie, Towards a Method of Dynamic Vocal Tract Shapes Generation by Combining Static 3D and Dynamic 2D MRI Speech Data, Interspeech 2019, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02181333

A. Ericsson, P. Aljabar, and D. Rueckert, Construction of a patient-specific atlas of the brain: Application to normal aging, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.480-483, 2008.

S. Erattakulangara and S. G. Lingala, Airway segmentation in speech MRI using the U-net architecture, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020.

B. Elie and Y. Laprie, Extension of the single-matrix formulation of the vocal tract: Consideration of bilateral channels and connection of self-oscillating models of the vocal folds with a glottal chink, Speech Communication, vol.82, pp.85-96, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01199792

M. Eslami, C. Neuschaefer-rube, and A. Serrurier, Automatic vocal tract landmark localization from midsagittal MRI data, Scientific Reports, vol.10, issue.1, pp.1-13, 2020.

C. Ericsdotter, Society Pages, Environment and History, vol.13, issue.4, pp.513-516, 2007.

M. Fu, M. S. Barlaz, J. L. Holtrop, J. L. Perry, D. P. Kuehn et al., High-frame-rate full-vocal-tract 3D dynamic speech imaging, Magnetic Resonance in Medicine, vol.77, issue.4, pp.1619-1629, 2016.

R. +-12]-andriy-fedorov, J. Beichel, J. Kalpathy-cramer, J. Finet, S. Fillion-robin et al., Dominique Jennings, Fiona Fennessy, Milan Sonka, et al. 3d slicer as an image computing platform for the quantitative imaging network, Magnetic resonance imaging, vol.30, issue.9, pp.1323-1341, 2012.

J. Michael, . Fagan, R. Stephen, J. M. Ell, E. Gilbert et al., Development of a (silent) speech recognition system for patients following laryngectomy, Medical engineering & physics, vol.30, issue.4, pp.419-425, 2008.

J. Frankel, M. Wester, and S. King, Articulatory feature recognition using dynamic Bayesian networks, Computer Speech & Language, vol.21, issue.4, pp.620-640, 2007.

Z. Fagyal, D. Kibbee, and F. Jenkins, French: A linguistic introduction, 2006.

D. Fohr, O. Mella, and D. Jouvet, De l'importance de l'homogénéisation des conventions de transcription pour l'alignement automatique de corpus oraux de parole spontanée, 8es Journées Internationales de Linguistique de Corpus (JLC2015), 2015.

Y. Fan, Y. Qian, F. Xie, and F. K. Soong, Tts synthesis with bidirectional lstm based recurrent neural networks, Fifteenth Annual Conference of the International Speech Communication Association, 2014.

F. Sidney-fels, K. Vogt, . Van-den, J. Doel, I. Lloyd et al., Artisynth: A biomechanical simulation platform for the vocal tract and upper airway, In International Seminar on Speech Production, vol.138, 2006.

M. Fu, J. Woo, Z. Liang, and B. P. Sutton, Spatiotemporal-atlas-based dynamic speech imaging, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, vol.9788, p.978804, 2016.

H. P. Greeley, E. Friets, J. P. Wilson, S. Raghavan, J. Picone et al., Detecting Fatigue From Voice Using Speech Recognition, 2006 IEEE International Symposium on Signal Processing and Information Technology, pp.567-571, 2006.

A. R. Greenwood, C. C. Goodyear, and P. A. Martin, Measurements of vocal tract shapes using magnetic resonance imaging, IEE Proceedings I Communications, Speech and Vision, vol.139, issue.6, p.553, 1992.

P. Kumar-ghosh and S. Narayanan, A generalized smoothness criterion for acoustic-to-articulatory inversion, The Journal of the Acoustical Society of America, vol.128, issue.4, pp.2162-2172, 2010.

S. Ioannis, D. Gousias, R. A. Rueckert, L. E. Heckemann, J. P. Dyet et al., Automatic segmentation of brain mris of 2-year-olds into 83 regions of interest, Neuroimage, vol.40, issue.2, pp.672-684, 2008.

M. Pravin, S. D. Ghate, and . Shirbhadurkar, Speech synthesis using syllable for marathi language, International Journal of Engineering and Research Technology

J. William and . Hardcastle, The use of electropalatography in phonetic research, Phonetica, vol.25, issue.4, pp.197-215, 1972.

Y. Noah-harari, Sapiens: A brief history of humankind. Random House, 2014.

J. Andrew, A. W. Hunt, and . Black, Unit selection in a concatenative speech synthesis system using a large speech database, Acoustics, Speech, and Signal Processing, vol.1, pp.373-376, 1996.

J. Hennig, K-space sampling strategies, European Radiology, vol.9, issue.6, pp.1020-1031, 1999.

J. Thomas and . Hixon, An electromagnetic method for transducing jaw movements during speech, The Journal of the Acoustical Society of America, vol.49, issue.2B, pp.603-606, 1971.

. Hjpa-+-03]-mark, S. Hasegawa-johnson, A. Pizza, J. Alwan, K. Setsu-alwan et al., Correlation between vocal tract length, body height, formant frequencies, and pitch frequency for the five japanese vowels uttered by fifteen male speakers, Thirteenth Annual Conference of the International Speech Communication Association, 2003.

S. Ian, P. Howard, and . Messum, Modeling the development of pronunciation in infant speech acquisition, 2011.

N. Hermant, P. Perrier, and Y. Payan, Human Tongue Biomechanical Modeling, Biomechanics of Living Organs, pp.395-411, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01652986

J. M. Heinz, K. N. Stevens-;-william-hardcastle, B. Vaxelaire, F. Gibbon, P. Hoole et al., Ema/epg study of lingual coarticulation in/kl/clusters. In 1st ETRW on Speech Production Modeling: From Control Strategies to Acoustics, Proceedings of the 5th International Congress on Acoustics, p.44, 1965.

S. Imai and Y. Abe, A low bit rate vocoder based on an improved cepstral method, The Journal of the Acoustical Society of America, vol.64, issue.S1, pp.S160-S160, 1978.

K. Johnson, P. Ladefoged, and M. Lindau, Individual differences in vowel production, The Journal of the Acoustical Society of America, vol.94, issue.2, pp.701-714, 1993.

I. Mohammed-a-jan, N. Marshall, and . Douglas, Effect of posture on upper airway dimensions in normal human, American Journal of Respiratory and Critical Care Medicine, vol.149, issue.1, pp.145-148, 1994.

H. Kawahara, STRAIGHT, exploitation of the other aspect of VOCODER: Perceptually isomorphic decomposition of speech sounds, Acoustical Science and Technology, vol.27, issue.6, pp.349-353, 2006.

A. Katsamanis, M. Black, G. Panayiotis, L. Georgiou, S. Goldstein et al., Robust long speech-text alignment, Proc. of workshop on new tools and methods for very-large scale phonetics research, 2011.

A. Katsamanis, E. Bresch, S. Vikram-ramanarayanan, and . Narayanan, Validating rt-mri based articulatory representations via articulatory recognition, Twelfth Annual Conference of the International Speech Communication Association, 2011.

J. W. David-p-kuehn and . Folkins, Korin Richmond, and Mirjam Wester. Speech production knowledge in automatic speech recognition, The Journal of the Acoustical Society of America, vol.19, issue.1, pp.723-742, 1982.

J. Bernd, V. Kröger, A. Graf-borttscheller, and . Lowit, Two and threedimensional visual articulatory models for pronunciation training and for treatment of speech disorders, Interspeech, 9th Annual Conference of the International Speech Communication Association, 2008.

J. Kim, N. Kumar, S. Lee, S. Narayanan-;-hideki-kawahara, T. Kitamura et al., Vocal tract length estimation based on vowels using a database consisting of 385 speakers and a database with mri-based vocal tract shape information, Fifteenth Annual Conference of the International Speech Communication Association, pp.222-225, 2014.

T. Kaneko, H. Kameoka, K. Tanaka, and N. Hojo, Cyclegan-VC2: Improved Cyclegan-based Non-parallel Voice Conversion, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.6820-6824, 2019.

J. Kim, S. Lee, and S. S. Narayanan, An exploratory study of manifolds of emotional speech, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010.

M. Kuklisova-murgasova, P. Aljabar, L. Srinivasan, S. J. Counsell, V. Doria et al., A dynamic 4D probabilistic atlas of the developing brain, NeuroImage, vol.54, issue.4, pp.2750-2763, 2011.

E. Kaan and T. Y. Swaab, The brain circuitry of syntactic comprehension, Trends in Cognitive Sciences, vol.6, issue.8, pp.350-356, 2002.

T. Kitamura, H. Takemoto, S. Adachi, and K. Honda, Transfer functions of solid vocal-tract models constructed from ATR MRI database of Japanese vowel production, Acoustical Science and Technology, vol.30, issue.4, pp.288-296, 2009.

J. Kim, A. Toutios, Y. Kim, Y. Zhu, S. Lee et al., Usc-emo-mri corpus: An emotional speech production database recorded by real-time magnetic resonance imaging, International Seminar on Speech Production (ISSP), p.226, 2014.

J. Bernd, R. Kröger, C. Winkler, B. Mooshammer, and . Pompino-marschall, Estimation of vocal tract area function from magnetic resonance imaging: Preliminary results, Proceedings of the 5th Seminar on Speech Production, pp.333-336, 2000.

Y. Laprie and M. Berger, Cooperation of regularization and speech heuristics to control automatic formant tracking, Speech Communication, vol.19, issue.4, pp.255-269, 1996.

Y. Laprie, B. Elie, A. Tsukanova, and P. Vuissoz, Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech, 2018 26th European Signal Processing Conference (EUSIPCO), 2018.
URL : https://hal.archives-ouvertes.fr/hal-01921928

P. Mathieu-labrunie, D. Badin, . Voit, A. Arun, J. Joseph et al., Automatic segmentation of speech articulators from real-time midsagittal mri based on supervised learning, Speech Communication, vol.99, pp.27-46, 2018.

Y. Laprie, B. Elie, A. Tsukanova, and P. Vuissoz, Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech, 2018 26th European Signal Processing Conference (EUSIPCO), 2018.
URL : https://hal.archives-ouvertes.fr/hal-01921928

Y. Laprie, B. Elie, A. Tsukanova, and P. Vuissoz, Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech, 2018 26th European Signal Processing Conference (EUSIPCO), pp.2110-2114, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01921928

J. M. Willem and . Levelt, Accessing words in speech production: Stages, processes and representations, 1992.

S. Liao, H. Jia, G. Wu, and D. Shen, A novel framework for longitudinal atlas construction with groupwise registration of subject image sequences, NeuroImage, vol.59, issue.2, pp.1275-1289, 2012.

]. Y. +-13a, M. Laprie, S. Loosvelt, E. Maeda, F. Sock et al., Articulatory copy synthesis from cine x-ray films, Interspeech 2013 (14th Annual Conference of the International Speech Communication Association), 2013.

[. Llm-+-13b]-yves-laprie, M. Loosvelt, S. Maeda, R. Sock, and F. Hirsch, Articulatory copy synthesis from cine x-ray films, 2013.

F. Lonchamp, II. PHONÉTIQUE DESCRIPTIVE, Phonétique et phonologie du judéo-espagnol de Bucarest, 1971.

E. F. Björn, J. E. Lindblom, and . Sundberg, T 1-weighted in vivo human whole brain mri dataset with an ultrahigh isotropic resolution of 250 µm, The Journal of the Acoustical Society of America, vol.50, issue.4B, pp.1-12, 1971.

B. P. Sajan-goud-lingala, M. E. Sutton, K. S. Miquel, and . Nayak, Recommendations for real-time speech mri, Journal of Magnetic Resonance Imaging, vol.43, issue.1, pp.28-44, 2016.

E. Lawson, J. M. Scobbie, and J. Stuart-smith, A Socio-Articulatory Study of Scottish Rhoticity, Sociolinguistics in Scotland

Y. Laprie, R. Sock, B. Vaxelaire, and B. Elie, Comment faire parler les images aux rayons X du conduit vocal, SHS Web of Conferences, vol.8, issue.3, pp.1285-1298, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01059887

I. Maddieson, Patterns of Sounds, 1984.

S. Maeda, A digital simulation method of the vocal-tract system, Speech Communication, vol.1, issue.3-4, pp.199-229, 1982.

S. Maeda, Compensatory Articulation During Speech: Evidence from the Analysis and Synthesis of Vocal-Tract Shapes Using an Articulatory Model, Speech Production and Speech Modelling, pp.131-149, 1990.

S. Maeda, On articulatory and acoustic variabilities, Journal of Phonetics, vol.19, issue.3-4, pp.321-331, 1991.

E. Moulines and F. Charpentier, Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones, Speech Communication, vol.9, issue.5-6, pp.453-467, 1990.

P. Mermelstein, Articulatory model for the study of speech production, The Journal of the Acoustical Society of America, vol.53, issue.4, pp.1070-1082, 1973.

S. Maeda and Y. Laprie, Vowel and prosodic factor dependent variations of vocal-tract length, InterSpeech-14th Annual Conference of the International Speech Communication Association-2013, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00836829

P. Martins, C. Oliveira, S. Silva, and A. Teixeira, Velar movement in european portuguese nasal vowels, Proc IberSpeech 2012 VII Jornadas en Tecnolog0?a del Habla and IIIIberian SLTech Workshop, pp.231-240, 2012.

. Shrikanth-s-narayanan, K. Abeer-a-alwan, and . Haker, Toward articulatory-acoustic models for liquid approximants based on mri and epg data. part i. the laterals, The Journal of the Acoustical Society of America, vol.101, issue.2, pp.1064-1077, 1997.

S. Narayanan, A. Toutios, V. Ramanarayanan, A. Lammert, J. Kim et al., Real-time magnetic resonance imaging and electromagnetic articulography database for speech production research (TC), The Journal of the Acoustical Society of America, vol.136, issue.3, pp.1307-1311, 2014.

S. Ouni and Y. Laprie, Modeling the articulatory space using a hypercube codebook for acoustic-to-articulatory inversion, The Journal of the Acoustical Society of America, vol.118, issue.1, pp.444-460, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00008682

C. Oliveira, P. Martins, S. Samuel, . Silva, and . Teixeira, An mri study of the oral articulation of european portuguese nasal vowels, INTERSPEECH, pp.2690-2693, 2012.

C. Oliveira, P. Martins, and A. Teixeira, Speech rate effects on european portuguese nasal vowels, Tenth Annual Conference of the International Speech Communication Association, 2009.

A. Ozerov, E. Vincent, and F. Bimbot, A General Flexible Framework for the Handling of Prior Information in Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.20, issue.4, pp.1118-1133, 2012.
URL : https://hal.archives-ouvertes.fr/inria-00536917

S. Joseph, . Perkell, H. Marc, M. A. Cohen, M. L. Svirsky et al., Electromagnetic midsagittal articulometer systems for transducing speech articulatory movements, The Journal of the Acoustical Society of America, vol.92, issue.6, pp.3078-3096, 1992.

L. Jamie, . Perry, P. David, . Kuehn, P. Bradley et al., Velopharyngeal structural and functional assessment of speech in young children using dynamic magnetic resonance imaging, The Cleft Palate-Craniofacial Journal, vol.54, issue.4, pp.408-422, 2017.

M. Proctor, A. Lammert, L. Goldstein, and S. Narayanan, Temporal analysis of articulatory speech errors using direct image analysis of real time magnetic resonance imaging., The Journal of the Acoustical Society of America, vol.128, issue.4, pp.2289-2289, 2010.

Y. Payan, P. Perrier, ;. Parthasarathy, J. L. Prince, M. Stone et al., Synthesis of vv sequences with a 2d biomechanical tongue model controlled by the equilibrium point hypothesis, The Journal of the Acoustical Society of America, vol.22, issue.2-3, pp.491-504, 1997.
URL : https://hal.archives-ouvertes.fr/hal-00085525

P. Perrier, Y. Payan, M. Zandipour, and J. Perkell, Influences of tongue biomechanics on speech movements during the production of velar stop consonants: A modeling study, The Journal of the Acoustical Society of America, vol.114, issue.3, pp.1582-1599, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00080414

M. Proctor, Y. Zhu, A. Lammert, A. Toutios, B. Sands et al., Click consonant production in khoekhoe: A real-time mri study, Khoisan Languages and Linguistics. Proc. 5th Intl. Symposium, pp.337-366, 2014.

. Lawrence-r-rabiner, Digital processing of speech signal. Digital Processing of Speech Signal, 1978.

S. Roekhaut, S. Brognaux, R. Beaufort, and T. Dutoit, eLite-HTS: Un outil TAL pour la génération de synthèse hmm en français, Démonstration aux Journées d'étude de la parole (JEP), 2014.

M. Ruthven, A. C. Freitas, R. Boubertakh, and M. E. Miquel, Application of radial GRAPPA techniques to single? and multislice dynamic speech MRI using a 16?channel neurovascular coil, Magnetic Resonance in Medicine, vol.82, issue.3, pp.390-400, 2019.

F. Roers, D. Mürbe, and J. Sundberg, Voice classification and vocal tract of singers: A study of x-ray images and morphology, The Journal of the Acoustical Society of America, vol.125, issue.1, pp.503-512, 2009.

A. Röbel and X. Rodet, Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation, Proc. of the 8 th Int. Conference on Digital Audio Effects (DAFx'05), 2005.

L. Romary, S. Salmon-alt, and G. Francopoulo, Standards going concrete, Proceedings of the Workshop on Enhancing and Using Electronic Dictionaries - ElectricDict '04, pp.22-28, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00100195

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. Hill, M. O. Leach et al., Nonrigid registration using free-form deformations: application to breast MR images, IEEE Transactions on Medical Imaging, vol.18, issue.8, pp.712-721, 1999.

J. Richard-c-rose, . Schroeter, S. Sondhi-;-vikram-ramanarayanan, M. Tilsen, J. Proctor et al., The potential role of speech production models in automatic speech recognition, The Journal of the Acoustical Society of America, vol.99, issue.3, pp.1699-1709, 1996.

C. Rumack, . Wilson, D. Charboneau, and . Levine, Diagnostic ultrasound, 2-volume set, 2010.

A. Serag, P. Aljabar, G. Ball, S. J. Counsell, J. P. Boardman et al., Erratum to Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression [NeuroImage 59/3(2012) 2255?2265], NeuroImage, vol.63, issue.2, p.998, 2012.

A. Serrurier and P. Badin, A three-dimensional articulatory model of the velum and nasopharyngeal wall based on MRI and CT data, The Journal of the Acoustical Society of America, vol.123, issue.4, pp.2335-2355, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00296604

A. Serrurier and P. Badin, A three-dimensional articulatory model of the velum and nasopharyngeal wall based on mri and ct data, The Journal of the Acoustical Society of America, vol.123, issue.4, p.30756, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00296604

M. Stone and E. P. Davis, A head and transducer support system for making ultrasound images of tongue/jaw movement, The Journal of the Acoustical Society of America, vol.98, issue.6, pp.3107-3112, 1995.

H. Christine, R. I. Shadle, and . Damper, Prospects for articulatory synthesis: A position paper, 4th ISCA Tutorial and Research Workshop (ITRW) on Speech Synthesis, 2001.

M. Stone, E. P. Davis, A. S. Douglas, M. Nessaiver, R. Gullapalli et al., Modeling the motion of the internal tongue from tagged cine-MRI images, The Journal of the Acoustical Society of America, vol.109, issue.6, pp.2974-2982, 2001.

D. Seghers, E. D?agostino, F. Maes, D. Vandermeulen, and P. R. Suetens, Construction of a Brain Template from MR Images Using State-of-the-Art Registration and Segmentation Techniques, Medical Image Computing and Computer-Assisted Intervention ? MICCAI 2004, pp.696-703, 2004.

H. Brad, E. A. Story, . Hoffman, and . Ingo-r-titze, Vocal tract imaging: a comparison of mri and ebct, Medical Imaging 1996: Physiology and Function from Multidimensional Images, vol.2709, pp.209-222, 1996.

J. Sotelo, S. Mehri, K. Kumar, J. F. Santos, K. Kastner et al., Char2wav: End-to-end speech synthesis, 2017.

S. M. Strassel, D. Miller, K. Walker, and C. Cieri, Shared resources for robust speech-to-text technology, 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003 -INTERSPEECH 2003, 2003.

D. Danny, H. Steinberg, and D. Nagata, Psycholinguistics: Language, mind and world, 2013.

A. Szabados and P. Perrier, Uncontrolled Manifolds in Vowel Production: Assessment with a Biomechanical Model of the Tongue, Interspeech 2016, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01390160

A. Caroline, W. S. Schneider, K. W. Rasband, and . Eliceiri, Nih image to imagej: 25 years of image analysis, Nature methods, vol.9, issue.7, p.671, 2012.

P. Saha, P. Srungarapu, and S. Fels, Towards Automatic Speech Identification from Vocal Tract Shape Dynamics in Real-time MRI, Interspeech 2018, 2018.

T. Sorensen, Z. Skordilis, A. Toutios, Y. Kim, Y. Zhu et al., Database of Volumetric and Real-Time Vocal Tract MRI for Speech Science, Interspeech 2017, pp.645-649, 2017.

S. Silva and A. Teixeira, Unsupervised segmentation of the vocal tract from real-time MRI sequences, Computer Speech & Language, vol.33, issue.1, pp.25-46, 2015.

S. Silva and A. Teixeira, Critical Articulators Identification from RT-MRI of the Vocal Tract, Interspeech 2017, pp.626-630, 2017.

H. Segi, T. Takagi, and T. Ito, A concatenative speech synthesis method using context dependent phoneme sequences with variable length as search units, Fifth ISCA Workshop on Speech Synthesis, 2004.

A. Zisis-iason-skordilis, J. Toutios, S. Töger, and . Narayanan, Estimation of vocal tract area function from volumetric magnetic resonance imaging, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.924-928, 2017.

Y. Stylianou, Applying the harmonic plus noise model in concatenative speech synthesis, IEEE Transactions on Speech and Audio Processing, vol.9, issue.1, pp.21-29, 2001.

. Protima-nomo-sudro, . Vikram, . Sr-mahadeva, and . Prasanna, Vowel onset point based characterization of velopharyngeal activity using imaging techniques, 2017 Twenty-third National Conference on Communications (NCC), pp.1-5, 2017.

H. Takemoto, Morphological Analyses of the Human Tongue Musculature for Three-Dimensional Modeling, Journal of Speech, Language, and Hearing Research, vol.44, issue.1, pp.95-107, 2001.

E. Bradley, . Treeby, T. Benjamin, and . Cox, k-wave: Matlab toolbox for the simulation and reconstruction of photoacoustic wave fields, Journal of biomedical optics, vol.15, issue.2, p.21314, 2010.

E. Bradley, B. T. Treeby, and . Cox, Modeling power law absorption and dispersion for acoustic propagation using the fractional laplacian, The Journal of the Acoustical Society of America, vol.127, issue.5, pp.2741-2748, 2010.

B. E. Treeby, J. Jaros, D. Rohrbach, and B. T. Cox, Modelling elastic wave propagation using the k-Wave MATLAB Toolbox, 2014 IEEE International Ultrasonics Symposium, 2014.

A. Tsukanova, K. Ioannis, A. Douros, Y. Shimorina, and . Laprie, Can static vocal tract positions represent articulatory targets in continuous speech? Matching static MRI captures against real-time MRI for the French language, International Congress on Phonetic Sciences, pp.5-9, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02181314

A. Tsukanova, B. Elie, Y. Laprie-;-hironori-takemoto, and T. Goto, Tatsuya Kitamura, Yukiko Nota, and Kikuo Maekawa. Speech organ contour extraction using real-time mri and machine learning method, International Seminar on Speech Production, pp.904-908, 2017.

H. Takemoto, K. Honda, S. Masaki, Y. Shimada, and I. Fujimoto, Measurement of temporal changes in vocal tract area function from 3D cine-MRI data, The Journal of the Acoustical Society of America, vol.119, issue.2, p.1037, 2006.

H. Takemoto, P. Mokhtari, and T. Kitamura, Acoustic analysis of the vocal tract during vowel production by finite-difference timedomain method, International Conference on Computational Processing of the Portuguese Language, vol.128, pp.306-317, 2010.

A. Toutios and S. S. Narayanan, Advances in real-time magnetic resonance imaging of the vocal tract for speech science and technology research, APSIPA Transactions on Signal and Information Processing, vol.5, 2016.

G. Touré and C. Vacher, Anatomic study of tongue architecture based on fetal histological sections, Surgical and Radiologic Anatomy, vol.28, issue.6, pp.547-552, 2006.

M. Uecker, S. Zhang, D. Voit, A. Karaus, K. Merboldt et al., Real-time MRI at a resolution of 20 ms, NMR in Biomedicine, vol.23, issue.8, pp.986-994, 2010.

B. Vaxelaire, Etude comparee des effets des variations de debit-lent, rapide-surles parametres articulatoires, a partir de la cineradiographie (sujets francais), 1993.

T. Vercauteren, X. Pennec, A. Perchant, and N. Ayache, Diffeomorphic demons: Efficient non-parametric image registration, NeuroImage, vol.45, issue.1, pp.S61-S72, 2009.
URL : https://hal.archives-ouvertes.fr/inserm-00349600

T. Ross and . Whitaker, A level-set approach to 3d reconstruction from range data, International journal of computer vision, vol.29, issue.3, pp.203-231, 1998.

H. Douglas, K. Whalen, . Iskarous, K. Mark, . Tiede et al., The haskins optically corrected ultrasound system (hocus), Journal of Speech, Language, and Hearing Research, 2005.

R. Samuel, R. Ward, J. Woo, . Lee, Z. Emi et al., A high-resolution atlas and statistical model of the vocal tract from structural mri, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol.38, issue.11, pp.47-60, 2005.

J. Westbury, P. Milenkovic, G. Weismer, and R. Kent, X?ray microbeam speech production database, The Journal of the Acoustical Society of America, vol.88, issue.S1, pp.S56-S56, 1990.

A. A. Wrench, A multi-channel/multi-speaker articulatory database for continuous speech recognition research. Phonus, 2000.

A. A. Wrench, A multichannel articulatory database and its application for automatic speech recognition, Proceedings 5 th Seminar of Speech Production, 2000.

. +-17]-yuxuan, . Wang, D. Skerry-ryan, Y. Stanton, R. J. Wu et al., Towards end-to-end speech synthesis, 2017.

S. Elliott, B. Wise, P. L. Wu, K. Tobing, and . Kobayashi, Full-wave nonlinear ultrasound simulation in an axisymmetric coordinate system using the discrete sine and cosine transforms, Tomoki Hayashi, and Tomoki Toda. Non-parallel voice conversion system with wavenet vocoder and collapsed speech suppression, pp.1374-1377, 2013.

Z. Wu, O. Watts, S. K. Merlin, ;. Woo, F. Xing et al., Speech map: A statistical multimodal atlas of 4d tongue motion during speech from tagged and cine mr images, International Conference on Information Processing in Medical Imaging, vol.6, pp.361-373, 2015.

F. Xing, J. L. Prince, M. Stone, V. J. Wedeen, G. El-fakhri et al., A four-dimensional motion field atlas of the tongue from tagged and cine magnetic resonance imaging, Medical Imaging 2017: Image Processing, vol.10133, 2017.

F. Xing, M. Stone, T. Goldsmith, J. L. Prince, G. El-fakhri et al., Atlas-Based Tongue Muscle Correlation Analysis From Tagged and High-Resolution Magnetic Resonance Imaging, Journal of Speech, Language, and Hearing Research, vol.62, issue.7, pp.2258-2269, 2019.

A. Paul, J. Yushkevich, H. C. Piven, R. G. Hazlett, S. Smith et al., User-guided 3d active contour segmentation of anatomical structures: significantly improved efficiency and reliability, IEEE transactions on medical imaging, vol.31, issue.3, pp.838-848, 2006.

C. Song, A. Zhu, and . Yuille, Region competition: Unifying snakes, region growing, and bayes/mdl for multiband image segmentation, IEEE transactions on pattern analysis and machine intelligence, vol.18, pp.884-900, 1996.