C. P. Browman and L. Goldstein, Articulatory phonology: An overview, Phonetica, vol.49, issue.3-4, pp.155-180, 1992.

O. Engwall, Are static MRI measurements representative of dynamic speech? results from a comparative study using MRI, EPG and EMA, Sixth International Conference on Spoken Language Processing, 2000.

A. C. Lammert, T. F. Quatieri, C. H. Shadle, and S. S. Narayanan, Speed accuracy tradeoffs in speech production, 2017.

Y. Laprie, B. Elie, A. Tsukanova, and P. Vuissoz, Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01921928

Q. Lin, Speech production theory and articulatory speech synthesis, The Journal of the Acoustical Society of America, vol.90, issue.4, pp.2203-2203, 1991.

D. G. Lowe, Object recognition from local scaleinvariant features. Computer vision, 1999. The proceedings of the seventh, IEEE international conference on, pp.1150-1157, 1999.

F. A. Mussa-ivaldi, N. Gantchev, and G. Gantchev, Motor primitives, force-fields and the equilibrium point theory. From Basic Motor Control to Functional Recovery, pp.392-398, 1999.

A. Niebergall, S. Zhang, E. Kunay, G. Keydana, M. Job et al., Real-time mri of speaking at a resolution of 33 ms: Undersampled radial flash with nonlinear inverse reconstruction. Magnetic Resonance in, Medicine, vol.69, issue.2, pp.477-485, 2013.

S. E. Öhman, Numerical model of coarticulation, The Journal of the Acoustical Society of America, vol.41, issue.2, pp.310-320, 1967.

P. Perrier, What goals for articulatory speech synthesis? The 11th International Seminar on Speech Production, 2017.

V. Ramanarayanan, S. Tilsen, M. Proctor, J. Töger, L. Goldstein et al., Analysis of speech production real-time mri, Computer Speech & Language, 2018.

V. Ramanarayanan, M. Van-segbroeck, and S. S. Narayanan, Directly data-derived articulatory gesture-like representations retain discriminatory information about phone categories, Computer speech & language, vol.36, pp.330-346, 2016.

S. Roekhaut, S. Brognaux, R. Beaufort, and T. Dutoit, eLite-HTS: Un outil TAL pour la génération de synthèse hmm en français, 2014.

Y. Rubner, C. Tomasi, and L. J. Guibas, The earth mover's distance as a metric for image retrieval, International journal of computer vision, vol.40, issue.2, pp.99-121, 2000.

E. Saltzman and J. Kelso, Skilled actions: a taskdynamic approach, Psychological review, vol.94, issue.1, p.84, 1987.

E. L. Saltzman and K. G. Munhall, A dynamical approach to gestural patterning in speech production, Ecological psychology, vol.1, issue.4, pp.333-382, 1989.

A. Toutios, T. Sorensen, K. Somandepalli, R. Alexander, and S. S. Narayanan, Articulatory synthesis based on real-time magnetic resonance imaging data, pp.1492-1496, 2016.

A. Tsukanova, B. Elie, and Y. Laprie, Articulatory speech synthesis from static context-aware articulatory targets, 2017-11th International Seminar on Speech Production, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01937950

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE transactions on image processing, vol.13, issue.4, pp.600-612, 2004.

Z. Wu, O. Watts, and S. King, Merlin: An open source neural network speech synthesis system, Proc. SSW, Sunnyvale, 2016.

S. Young, G. Evermann, M. Gales, T. Hain, D. Kershaw et al., others, 2002. The HTK book. Cambridge university engineering department 3, p.175