A. M. , B. Ben-kheder-w, and R. S. Kahn-j, Phonetic content impact on forensic voice comparison, Spoken Language Technology Workshop (SLT), pp.210-217, 2016.

A. G. Brizan, D. G. , M. M. Morales, M. R. Syed-a, and . Rosenberg-a, Automatic recognition of unified parkinson's disease rating from speech with acoustic, i-vector and phonotactic features, Proceedings of Interspeech'15, 2015.

A. C. Balaguer, M. Farinas, J. Fredouille, C. Gaillard, P. Ghio et al., Carcinologic speech severity index project : A database of speech disorders productions to assess quality of life related to speech after cancer, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2018), 2018.

C. H. Cunningham-s, C. Fox, and . Green-p.-&-hain-t, A comparative study of adaptive, automatic recognition of disordered speech, Proceedings of Interspeech'12, 2012.

D. N. Kenny-p, . Dehak-r, . &. Dumouchel-p, and . Ouellet-p, Front-end factor analysis for speaker verification, IEEE Transactions on Audio, Speech, and Language Processing, vol.19, issue.4, pp.788-798, 2011.

G. N. Orozco-arroyave, J. R. Haro-l, and . Dehak-n.-&-nöth-e, Evaluation of the neurological state of people with parkinson's disease using i-vectors, Proceedings of Interspeech'17, 2017.

G. A. André and C. Teston-b.-&-cavé-c, Perceval : une station automatisée de tests de perception et d'évaluation auditive et visuelle. Travaux interdisciplinaires du Laboratoire parole et langage d, vol.22, pp.115-133, 2003.

G. A. Lalain, M. Giusti, L. Pouchoulin, G. , R. D. Fredouille et al.,

W. V. , Une mesure d'intelligibilité par décodage acoustico-phonétique de pseudo-mots dans le cas de parole atypique, Journées d'Etude sur la Parole (JEP), 2018.

K. T. Westin and J. &. Dougherty-m, Classification of speech intelligibility in parkinson's disease, Biocybernetics and Biomedical Engineering, vol.34, issue.1, pp.35-45, 2014.

L. I. Ben-kheder-w, C. &. Fredouille, and . Meunier-c, Automatic prediction of speech evaluation metrics for dysarthric speech, Proceedings of Interspeech'17, pp.1834-1838, 2017.

L. I. Fredouille and C. &. Meunier-c, Automatic detection of phone-based anomalies in dysarthric speech, ACM Transactions on accessible computing, vol.6, issue.3, p.24, 2015.

L. A. , B. G. Fauve-b, L. Lévy, C. , L. H. Mason et al., Alize 3.0-open source toolkit for state-of-the-art speaker recognition, Proceedings of Interspeech'13, pp.2768-2772, 2013.

M. D. Lleida, E. Green, P. Christensen, and H. Ortega-a.-&-miguel-a, Intelligibility assessment and speech recognizer word accuracy rate prediction for dysarthric speakers in a factor analysis subspace, ACM Transactions on Accessible Computing (TACCESS), vol.6, issue.3, p.10, 2015.

M. D. Scheffer, N. G. Fauve-b, and &. , A straightforward and efficient implementation of the factor analysis model for speaker verification, pp.1242-1245, 2007.
URL : https://hal.archives-ouvertes.fr/hal-01318480

M. C. Martens-j.-p, . Van-nuffelen-g, and . De-bodt-m, Automated intelligibility assessment of pathological speech using phonological features, EURASIP Journal on Advances in Signal Processing, issue.1, pp.1-9, 2009.

S. A. Schölkopf-b, A tutorial on support vector regression, Statistics and computing, vol.14, issue.3, pp.199-222, 2004.

V. K. , i-vectors in speech processing applications : a survey, International Journal of Speech Technology, vol.18, issue.4, pp.529-546, 2015.

W. J. Kothalkar, P. V. , and C. B. Heitzman-d, Towards automatic detection of amyotrophic lateral sclerosis from speech acoustic and articulatory samples, Proceedings of Interspeech'16, 2016.