[. Aarsland, The spectrum of neuropsychiatric symptoms in patients with early untreated Parkinson's disease, Neurosurgery & Psychiatry, vol.80, issue.8, pp.928-930, 2009.

A. , Frequency of levodoparelated dyskinesias and motor fluctuations as estimated from the cumulative literature, Neurology, vol.57, issue.3, pp.448-458, 2001.

. Andrews, Bootstrapping for speaker recognition, INTERSPEECH, 2000.

A. , Pathomechanisms and compensatory efforts related to Parkinsonian speech, NeuroImage : Clinical, vol.4, pp.82-97, 2014.

I. Arnulf-;-arnulf, REM sleep behavior disorder : Motor manifestations and pathophysiology, Movement Disorders, vol.27, issue.6, pp.677-689, 2012.
URL : https://hal.archives-ouvertes.fr/inserm-00684707

. Arora, Detecting and monitoring the symptoms of Parkinson's disease using smartphones : A pilot study, Parkinsonism & related disorders, vol.21, issue.6, pp.650-653, 2015.

[. Bardinet, A three-dimensional histological atlas of the human basal ganglia. II. Atlas deformation strategy and evaluation in deep brain stimulation for Parkinson disease, Journal of Neurosurgery, vol.110, issue.2, pp.208-227, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00616029

[. Barone, The PRIAMO study : A multicenter assessment of nonmotor symptoms and their impact on quality of life in Parkinson's disease, vol.24, pp.1641-1649, 2009.

[. Benba, Voice analysis for detecting persons with Parkinson's disease using MFCC and VQ, The 2014 international conference on circuits, systems and signal processing, pp.23-25, 2014.

[. Benba, Detecting Patients with Parkinson's disease using Mel Frequency Cepstral Coefficients a nd Support Vector Machines, International Journal on Electrical Engineering and Informatics, vol.7, issue.2, pp.297-307, 2015.

[. Benba, Analysis of multiple types of voice recordings in cepstral domain using MFCC for discriminating between patients with Parkinson's disease and healthy people, International Journal of Speech Technology, vol.19, issue.3, pp.449-456, 2016.

, Discriminating Between Patients With Parkinson's and Neurological Diseases Using Cepstral Analysis, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.24, issue.10, pp.1100-1108, 2016.

, Using Human Factor Cepstral Coefficient on Multiple Types of Voice Recordings for Detecting Patients with Parkinson's Disease, IRBM, vol.38, issue.6, pp.346-351, 2017.

, A Tutorial on Text-Independent Speaker Verification, EURASIP Journal on Advances in Signal Processing, issue.4, p.101962, 2004.

, ACCURATE SHORT-TERM ANALYSIS OF THE FUN-DAMENTAL FREQUENCY AND THE HARMONICS-TO-NOISE RATIO OF A SAM-PLED SOUND, Proceedings of the Institute of Phonetic Sciences, vol.17, pp.97-110, 1993.

P. Boersma and D. Weenink, PRAAT, a system for doing phonetics by computer, Glot international, vol.5, pp.341-345, 2001.

S. Boll-;-boll, Suppression of acoustic noise in speech using spectral subtraction, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.27, issue.2, pp.113-120, 1979.

, Gastric alpha-synuclein immunoreactive inclusions in Meissner's and Auerbach's plexuses in cases staged for Parkinson's disease-related brain pathology, American Journal of Neuroradiology, vol.36, issue.2, pp.197-211, 2003.

L. Breiman and . Brunato, Supervised and unsupervised machine learning for the detection, monitoring and management of Parkinson's disease from passive mobile phone data. In : Predicting Parkinson's Disease Progression with Smartphone Data. Kaggle Competition, Machine Learning, vol.24, pp.123-140, 1996.

, Prion-like transmission of protein aggregates in neurodegenerative diseases, Nature Reviews Molecular Cell Biology, vol.11, issue.4, pp.301-307, 2010.

Y. ;. Bühlmann, P. Bühlmann, and B. Yu, Analyzing Bagging. The Annals of Statistics, vol.30, pp.927-961, 2002.

J. P. Campbell-;-campbell, Speaker recognition : a tutorial, Proceedings of the IEEE, vol.85, issue.9, pp.1437-1462, 1997.

, Support vector machines using GMM supervectors for speaker verification, IEEE Signal Processing Letters, vol.13, issue.5, pp.308-311, 2006.

[. Chen, Meta-analyses on prevalence of selected Parkinson's nonmotor symptoms before and after diagnosis, Translational Neurodegeneration, vol.4, issue.1, p.1, 2015.

[. Countryman, Parkinson's Disease : Speaking Out. National Parkinson Foundation, 2003.

L. Frederic, Differential Diagnostic Patterns of Dysarthria, Journal of Speech and Hearing Research, vol.12, issue.2, pp.246-269, 1969.

M. Davis, S. Davis, and P. Mermelstein, Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.28, issue.4, pp.357-366, 1980.

. [de-cock, Restoration of normal motor control in Parkinson's disease during REM sleep, Brain, vol.130, issue.2, pp.450-456, 2007.

D. Lau, B. Lau, L. M. Breteler, and M. M. , Epidemiology of Parkinson's disease, The Lancet Neurology, vol.5, issue.6, pp.525-535, 2006.

L. Xavier, , 2019.

, Sexual Dimorphism Within Brain Regions Controlling Speech Production. Frontiers in Neuroscience, vol.13

[. Dehak, Front End Factor Analysis For Speaker Verification, IEEE TRANSACTIONS ON AUDIO, p.13, 2011.

[. Dibazar, Feature analysis for automatic detection of pathological speech, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society, vol.1, pp.182-183, 2002.

[. Dorsey, Projected number of people with Parkinson disease in the most populous nations, Neurology, vol.68, issue.5, pp.384-386, 2005.

[. Drissi, Diagnosis of Parkinson's Disease based on Wavelet Transform and Mel Frequency Cepstral Coefficients, International Journal of Advanced Computer Science and Applications, vol.10, issue.3, 2019.

[. Elgh, Cognitive function in early Parkinson's disease : a population-based study, European Journal of Neurology, vol.16, issue.12, pp.1278-1284, 2009.

J. M. Fearnley and A. J. Lees, Ageing and Parkinson's disease : substantia nigra regional selectivity, Brain : A Journal of Neurology, vol.114, pp.2283-2301, 1991.

[. Fraile, MFCC-based remote pathology detection on speech transmitted through the telephone channel, Proc Biosignals, 2009.

[. Fraile, Automatic Detection of Laryngeal Pathologies in Records of Sustained Vowels by Means of Mel-Frequency Cepstral Coefficient Parameters and Differentiation of Patients by Sex, Folia Phoniatrica et Logopaedica, vol.61, issue.3, pp.146-152, 2009.

[. Friedman, Springer series in statistics Springer, vol.1, 2001.

. Garcia-ospina, Phonological i-Vectors to Detect Parkinson's Disease, Text, Speech, and Dialogue, pp.462-470, 2018.

[. Gaurav, LONGITUDINAL VARIATIONS IN NEUROMELANIN MRI SIGNAL IN PARKINSON'S DISEASE, 2019.

[. Ghio, A. Pinto-;-ghio, and S. Pinto, Résonance sonore et cavités supralaryngée, Les Dysarthries, pp.101-110, 2007.

J. Gil, D. Gil, and M. Johnson, Diagnosing Parkinson by using Artificial Neural Networks and Support Vector Machines, Global Journal of Computer Science and Technology, p.9, 2009.

. Godino-llorente, Dimensionality Reduction of a Pathological Voice Quality Assessment System Based on Gaussian Mixture Models and Short-Term Cepstral Parameters, IEEE Transactions on Biomedical Engineering, vol.53, issue.10, pp.1943-1953, 2006.

[. Godino-llorente, G. Godino-llorente, J. Gómez-vilda, and P. , Automatic Detection of Voice Impairments by Means of Short-Term Cepstral Parameters and Neural Network Based Detectors, IEEE Transactions on Biomedical Engineering, vol.51, issue.2, pp.380-384, 2004.

[. Goetz, Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) : Process, format, and clinimetric testing plan. Movement Disorders, vol.22, pp.41-47, 2007.

. Goldman, J. Holden-;-goldman, and S. Holden, Parkinson's Disease, Encyclopedia of Mental Health, pp.242-248, 2016.

[. Graff, Switchboard-2 Phase I, 1998.

[. Graff, , 2001.

[. Graff, , 2004.

[. Grosz, Assessing the Degree of Nativeness and Parkinson's Condition Using Gaussian Processes and Deep Rectifier Neural Networks, p.5, 2015.

. Gómez-vilda, Parkinson Disease Detection from Speech Articulation Neuromechanics, Frontiers in Neuroinformatics, p.11, 2017.

[. Haas, Premotor biomarkers for Parkinson's disease-a promising direction of research, Transl Neurodegener, vol.1, issue.1, p.11, 2012.

[. Haaxma, Gender differences in Parkinson's disease, Journal of Neurology, issue.8, pp.819-824, 2007.

A. ;. Halawani, S. M. Halawani, and A. Ahmad, Ensemble methods for prediction of Parkinson disease, Intelligent Data Engineering and Automated Learning-IDEAL 2012, pp.516-521, 2012.

. Harel, Variability in fundamental frequency during speech in prodromal and incipient Parkinson's disease : A longitudinal case study, Brain and Cognition, vol.56, issue.1, pp.24-29, 2004.

. Hawkes, Olfactory dysfunction in Parkinson's disease, Neurosurgery, and Psychiatry, vol.62, issue.5, pp.436-446, 1997.

[. Heigold, End-to-end text-dependent speaker verification, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5115-5119, 2016.

[. Hemmerling, Automatic Detection of Parkinson's Disease Based on Modulated Vowels, INTERSPEECH, pp.1190-1194, 2016.

Y. Hoehn, M. Hoehn, and M. D. Yahr, Parkinsonism : onset, progression and mortality, Neurology, vol.17, issue.5, pp.427-442, 1967.

O. Hornykiewicz, Biochemical aspects of Parkinson's disease, Neurology, vol.51, issue.2, p.2, 1998.

. Hughes, Accuracy of clinical diagnosis of idiopathic Parkinson's disease : a clinico-pathological study of 100 cases, Neurosurgery & Psychiatry, vol.55, issue.3, pp.181-184, 1992.

[. Huh, Differences in early speech patterns between Parkinson variant of multiple system atrophy and Parkinson's disease, Brain and Language, vol.147, pp.14-20, 2015.

. Iansek, Interaction of the basal ganglia and supplementary motor area in the elaboration of movement, Advances in Psychology, vol.111, pp.37-59, 1995.

[. Iranzo, Neurodegenerative Disorder Risk in Idiopathic REM Sleep Behavior Disorder : Study in 174 Patients, PLoS ONE, issue.2, p.9, 2014.

A. Jafari-;-jafari, Classification of Parkinson's Disease Patients using Nonlinear Phonetic Features and Mel-Frequency Cepstral Analysis, Biomedical Engineering : Applications, vol.25, issue.04, p.1350001, 2013.

J. Jankovic, Pathophysiology And Clinical Assessment Of Parkinsonian Symptoms And Signs, Handbook of Parkinson's Disease, 2003.

[. Jeancolas, Automatic detection of early stages of Parkinson's disease through acoustic voice analysis with mel-frequency cepstral coefficients, 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pp.1-6, 2017.

[. Jeancolas, Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson's Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models, Interspeech 2019, pp.3033-3037, 2019.

[. Jeancolas, Analyse de la Voix au Stade Débutant de la Maladie de Parkinson et Corrélations avec Analyse clinique et Neuroimagerie, Journées d'Etude sur la TéléSanté, 2019.

[. Jeancolas, L'analyse de la voix comme outil de diagnostic précoce de la maladie de Parkinson :état de l'art, CORESA 2016 : 18e Edition COmpressions et REprésentation des Signaux Audiovisuels, pp.113-121, 2016.

[. Jiang, Glottographic Measures Before and After Levodopa Treatment in Parkinson's Disease, The Laryngoscope, vol.109, issue.8, pp.1287-1294, 1999.

[. Jung, Sex Differences in White Matter Pathways Related to Language Ability, Frontiers in Neuroscience, p.13, 2019.

. Kapoor, T. Sharma-;-kapoor, and R. K. Sharma, Parkinson's disease diagnosis using Mel-frequency cepstral coefficients and vector quantization, International Journal of Computer Applications, vol.14, issue.3, pp.43-46, 2011.

. Kenny, Eigenvoice modeling with sparse training data, IEEE Transactions on Speech and Audio Processing, vol.13, issue.3, pp.345-354, 2005.

. Kenny, Joint Factor Analysis Versus Eigenchannels in Speaker Recognition, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.4, pp.1435-1447, 2007.

. Kenny, New MAP Estimators for Speaker Recognition, INTERSPEECH, p.4, 2003.

[. Kharroubi, Combining GMM's with Suport Vector Machines for Text-independent Speaker Verification, p.5, 2001.

[. Khojasteh, Parkinson's Disease Diagnosis Based on Multivariate Deep Features of Speech Signal, IEEE Life Sciences Conference (LSC), pp.187-190, 2018.

A. Kibleur, Cartographie corticale parélectroencéphalographie des effets de la stimulation cérébrale profonde chez les patients souffrant de troubles psychiatriques réfractaires et les patients parkinsoniens, 2016.

L. Koenig-;-koenig and R. Kohavi, A study of cross-validation and bootstrap for accuracy estimation and model selection, Ijcai, vol.14, pp.1137-1145, 1995.

[. Kulisevsky, Prevalence and correlates of neuropsychiatric symptoms in Parkinson's disease without dementia, Movement Disorders, vol.23, issue.13, pp.1889-1896, 2008.

K. , L. ;. Kyung, Y. J. Lee, and H. S. , Bootstrap and aggregating VQ classifier for speaker recognition, Electronics Letters, vol.35, issue.12, pp.973-974, 1999.

A. Larcher, Modèles acoustiques pour la reconnaissance du locuteur. Habilitationà diriger des recherches, 2018.

[. Lebouvier, Colonic Biopsies to Assess the Neuropathology of Parkinson's Disease and Its Relationship with Symptoms, PLoS ONE, vol.5, issue.9, 2010.

[. Lei, A NOVEL SCHEME FOR SPEAKER RECOGNITION USING A PHONETICALLY-AWARE DEEP NEURAL NETWORK, IEEE International Conference on Acoustics, Speech, and Signal Processing, p.5, 2014.

[. Li, L. Li, and T. F. Zheng, Gender-dependent feature extraction for speaker recognition, 2015 IEEE China Summit and International Conference on Signal and Information Processing, pp.509-513, 2015.

[. Li, Validation of a new REM sleep behavior disorder questionnaire (RBDQ-HK), Sleep Medicine, vol.11, issue.1, pp.43-48, 2010.

[. Lim, Overview of the Extranigral Aspects of Parkinson Disease, ARCH NEUROL, vol.66, issue.2, p.6, 2009.

[. Little, Suitability of Dysphonia Measurements for Telemonitoring of Parkinson&amp ;#x0027 ;s Disease, IEEE Transactions on Biomedical Engineering, vol.56, issue.4, pp.1015-1022, 2009.

J. Locco, La production des occlusives dans la maladie de Parkinson, 2005.

[. Maillard, Cross-validation improved by aggregation : Agghoo. hal, p.21, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01585595

[. Malyska, Automatic dysphonia recognition using biologically-inspired amplitude-modulation features, Acoustics, Speech, and Signal Processing, vol.1, p.873, 2005.

W. Meissner-;-meissner, When does Parkinson's disease begin ? From prodromal disease to motor signs, Revue Neurologique, vol.168, issue.11, pp.809-814, 2012.

C. Meunier-;-meunier, F. Moisan, and . En, Phonétique acoustique, ETÉVOLUTION JUSQU'EN 2030, pp.8-9, 2007.

. Moro-velázquez, Analysis of speaker recognition methodologies and the influence of kinetic changes to automatically detect Parkinson's Disease, Applied Soft Computing, vol.62, pp.649-666, 2018.

C. Murphy, Prevalence of Olfactory Impairment in Older Adults, JAMA, vol.288, issue.18, p.2307, 2002.

J. Müller, Progression of dysarthria and dysphagia in postmortem-confirmed parkinsonian disorders, Archives of Neurology, vol.58, issue.2, pp.259-264, 2001.

[. Nagrani, VoxCeleb : A Large-Scale Speaker Identification Dataset, pp.2616-2620, 2017.

[. Narayana, Neural correlates of efficacy of voice therapy in Parkinson's disease identified by performance-correlation analysis, Human Brain Mapping, vol.31, issue.2, pp.222-236, 2010.

[. Narayana, A Non-Invasive Imaging Approach to Understanding Speech Changes following Deep Brain Stimulation in Parkinson's Disease. American journal of speech-language pathology, American Speech-Language-Hearing Association, vol.18, issue.2, pp.146-161, 2009.

[. Novotný, Automatic Evaluation of Articulatory Disorders in Parkinson's Disease, Speech, and Language Processing, vol.22, pp.1366-1378, 2014.

. Orozco-arroyave, New Spanish Speech Corpus Database for the Analysis of People Suffering from Parkinson's Disease, Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), 2014.

. Orozco-arroyave, Characterization Methods for the Detection of Multiple Voice Disorders : Neurological, Functional, and Laryngeal Diseases, IEEE Journal of Biomedical and Health Informatics, vol.19, issue.6, pp.1820-1828, 2015.

. Orozco-arroyave, Automatic detection of Parkinson's disease from words uttered in three different languages, INTERSPEECH, pp.1573-1577, 2014.

. Orozco-arroyave, Voiced/unvoiced transitions in speech as a potential bio-marker to detect parkinson's disease, INTERSPEECH, pp.95-99, 2015.

. Orozco-arroyave, Automatic detection of Parkinson's disease in running speech spoken in three different languages, The Journal of the Acoustical Society of America, vol.139, issue.1, pp.481-500, 2016.

. Orozco-arroyave, Towards an automatic monitoring of the neurological state of Parkinson's patients from speech, pp.6490-6494, 2016.

H. Ozkan, A Comparison of Classification Methods for Telediagnosis of Parkinson's Disease, Entropy, vol.18, issue.4, p.115, 2016.

S. Parveen and A. Qadeer, SPEAKER RECOGNITION WITH RECURRENT NEURAL NETWORKS, ICSLP, p.4, 2000.

[. Pedersen, Prevalence and clinical correlates of apathy in Parkinson's disease : A community-based study, Parkinsonism & Related Disorders, vol.15, issue.4, pp.295-299, 2009.

. Peelaerts, Alpha-Synuclein strains cause distinct synucleinopathies after local and systemic administration, Nature, vol.522, issue.7556, pp.340-344, 2015.

. Pelecanos, J. W. Sridharan-;-pelecanos, and S. Sridharan, Feature warping for robust speaker verification, 2001.

, Decreased color discrimination and contrast sensitivity in Parkinson's disease, Journal of the Neurological Sciences, vol.8, issue.5, pp.7-11, 2000.

[. Pinto, Stimulation of the pedunculopontine nucleus area in Parkinson's disease : effects on speech and intelligibility, Brain, vol.137, issue.10, pp.2759-2772, 2014.

[. Pinto, La dysarthrie au cours de la maladie de Parkinson. Histoire naturelle de ses composantes : dysphonie, dysprosodie et dysarthrie, Revue Neurologique, vol.166, issue.10, pp.800-810, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01616010

[. Ponsen, Idiopathic hyposmia as a preclinical sign of Parkinson's disease, Annals of Neurology, vol.56, issue.2, pp.173-181, 2004.

R. B. Postuma, Voice changes in prodromal Parkinson's disease -is a new biomarker within earshot ? Sleep Medicine, 2015.

, How does parkinsonism start ? Prodromal parkinsonism motor changes in idiopathic REM sleep behaviour disorder, Brain, vol.135, issue.6, pp.1860-1870, 2012.

[. Povey, Signes de maladie de Parkinson idiopathique, IEEE 2011 Workshop on Automatic Speech Recognition and Understanding, vol.35, pp.526-529, 2011.

S. J. Prince and . Pyatigorskaya, Probabilistic Linear Discriminant Analysis for, Inferences About Identity, 2007.

, Comparative Study of MRI Biomarkers in the Substantia Nigra to Discriminate Idiopathic Parkinson Disease

, Intensive voice treatment (LSVT R ) for patients with Parkinson's disease : a 2 year follow up, Neurosurgery & Psychiatry, vol.71, issue.4, pp.493-498, 2001.

[. Rektorova, Functional neuroanatomy of vocalization in patients with Parkinson's disease, Journal of the Neurological Sciences, vol.313, issue.1-2, pp.7-12, 2012.

D. A. Reynolds-;-reynolds, A Gaussian mixture modeling approach to textindependent speaker identification, 1992.

, Speaker Verification Using Adapted Gaussian Mixture Models, Digital Signal Processing, vol.10, issue.1-3, pp.19-41, 2000.

R. Reynolds, D. A. Reynolds, and R. C. Rose, Robust text-independent speaker identification using Gaussian mixture speaker models, IEEE Trans. Speech and Audio Processing, vol.3, pp.72-83, 1995.

[. Ribeiro, Dopaminergic Function and Dopamine Transporter Binding Assessed With Positron Emission Tomography in Parkinson Disease, Archives of Neurology, vol.59, issue.4, pp.580-586, 2002.

G. Richard, Analyse des signaux audiofréquences -Indexation audio, 2016.

. Rodriguez-oroz, Initial clinical manifestations of Parkinson's disease : features and pathophysiological mechanisms, The Lancet Neurology, vol.8, issue.12, pp.1128-1139, 2009.

[. Rusz, Quantitative acoustic measurements for characterization of speech and voice disorders in early untreated Parkinson's disease, The Journal of the Acoustical Society of America, vol.129, issue.1, p.350, 2011.

[. Rusz, Imprecise vowel articulation as a potential early marker of Parkinson's disease : Effect of speaking task, The Journal of the Acoustical Society of America, vol.134, issue.3, pp.2171-2181, 2013.

[. Rusz, Quantitative assessment of motor speech abnormalities in idiopathic rapid eye movement sleep behaviour disorder, Sleep Medicine, 2015.

[. Rusz, Smartphone Allows Capture of Speech Abnormalities Associated With High Risk of Developing Parkinson's Disease, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.26, issue.8, pp.1495-1507, 2018.

[. Rusz, Acoustic assessment of voice and speech disorders in Parkinson's disease through quick vocal test, Movement Disorders, vol.26, issue.10, pp.1951-1952, 2011.

[. Rusz, Evaluation of speech impairment in early stages of Parkinson's disease : a prospective study with the role of pharmacotherapy, Journal of Neural Transmission, vol.120, issue.2, pp.319-329, 2013.

[. Sachin, Functional mapping in PD and PSP for sustained phonation and phoneme tasks, Journal of the Neurological Sciences, vol.273, issue.1-2, pp.51-56, 2008.

[. Sadjadi, The 2016 NIST Speaker Recognition Evaluation, INTERSPEECH, 2017.

[. Sakar, Collection and Analysis of a Parkinson Speech Dataset With Multiple Types of Sound Recordings, IEEE Journal of Biomedical and Health Informatics, vol.17, issue.4, pp.828-834, 2013.

[. Sakar, Analyzing the effectiveness of vocal features in early telediagnosis of Parkinson's disease, PLOS ONE, vol.12, issue.8, p.182428, 2017.

[. Santamaria, Parkinson's disease with depression, Neurology, vol.36, issue.8, p.1130, 1986.

[. Schenck, Delayed emergence of a parkinsonian disorder or dementia in 81% of older males initially diagnosed with idiopathic REM sleep behavior disorder (RBD) : 16 year update on a previously reported series, 2013.

, The INTERSPEECH 2015 Computational Paralinguistics Challenge : Nativeness, Parkinson's & Eating Condition. In INTERSPEECH, p.5, 2015.

S. Skodda-;-skodda, Steadiness of syllable repetition in early motor stages of Parkinson's disease, Biomedical Signal Processing and Control, vol.17, pp.55-59, 2015.

[. Skodda, Impairment of Vowel Articulation as a Possible Marker of Disease Progression in Parkinson's Disease, PLoS ONE, vol.7, issue.2, p.32132, 2012.

, Instability of syllable repetition in Parkinson's disease-Impairment of automated speech performance ?, Basal Ganglia, vol.3, issue.1, pp.33-37, 2013.

[. Snyder, Spoken Language Recognition using X-vectors, Odyssey 2018 The Speaker and Language Recognition Workshop, pp.105-111, 2018.

, Deep Neural Network Embeddings for Text-Independent Speaker Verification, pp.999-1003, 2017.

, X-Vectors : Robust DNN Embeddings for Speaker Recognition, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5329-5333, 2018.

, Deep neural network-based speaker embeddings for end-to-end speaker verification, 2016 IEEE Spoken Language Technology Workshop (SLT), pp.165-170, 2016.

, A vector quantization approach to speaker recognition, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol.10, pp.387-390, 1985.

, Neuromelanin detection by magnetic resonance imaging (MRI) and its promise as a biomarker for Parkinson's disease, 2018.

. Sáenz-lechón, Loss of olfaction in de novo and treated Parkinson's disease : Possible implications for early diagnosis, Biomedical Signal Processing and Control, vol.1, issue.2, pp.75-86, 2001.

. Tsanas, Using the cellular mobile telephone network to remotely monitor parkinsons disease symptom severity, IEEE Transactions on Biomedical Engineering, 2012.

. Tsanas, Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity, Journal of The Royal Society Interface, vol.8, issue.59, pp.842-855, 2011.

. Tsanas, Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease, IEEE Transactions on Biomedical Engineering, vol.59, issue.5, pp.1264-1271, 2012.

. Vaiciukynas, Detecting Parkinson's disease from sustained phonation and speech signals, PLOS ONE, vol.12, issue.10, p.185613, 2017.

[. Variani, Deep neural networks for small footprint text-dependent speaker verification, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4052-4056, 2014.

[. Viallet, , 2010.

. Maladie-de-parkinson, F. Viallet, and B. Teston, La dysarthrie dans la maladie de Parkinson, aspects cliniques, diagnostiques et thérapeutiques. EMC. [Viallet and Teston, pp.169-174, 2007.

. Vásquez-correa, Convolutional Neural Network to Model Articulation Impairments in Patients with Parkinson's Disease, INTERSPEECH, pp.314-318, 2017.

. Vásquez-correa, Effect of acoustic conditions on algorithms to detect Parkinson's disease from speech, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5065-5069, 2017.

[. Weintraub, Impulse Control Disorders in Parkinson Disease : A Cross-Sectional Study of 3090 Patients, Archives of Neurology, issue.5, p.67, 2010.

[. Wu, Influence of sampling rate on voice analysis for assessment of Parkinson's disease, The Journal of the Acoustical Society of America, vol.144, issue.3, pp.1416-1423, 2018.

[. Zhang, DeepVoice : A voiceprintbased mobile health framework for Parkinson's disease identification, 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), pp.214-217, 2018.

Y. N. Zhang, Can a Smartphone Diagnose Parkinson Disease ? A Deep Neural Network Method and Telediagnosis System Implementation, 2017.

?. L. Jeancolas, G. Mangone, J. C. Corvol, M. Vidailhet, S. Lehéricy et al., Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson's Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models, Interspeech, pp.3033-3070, 2019.

?. L. Jeancolas, G. Mangone, N. Villain, R. Gaurav, M. O. Habert et al., Analyse de La Voix Au Stade Débutant de La Maladie de Parkinson et Corrélations Avec Analyse Clinique et Neuroimagerie, Journées d'Etude Sur La TéléSanté, 2019.

?. L. Jeancolas, H. Benali, B. E. Benkelfat, G. Mangone, J. C. Corvol et al., Automatic Detection of Early Stages of Parkinson's Disease through Acoustic Voice Analysis with Mel-Frequency Cepstral Coefficients, 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pp.1-6, 2017.

?. L. Jeancolas, D. Petrovska-delacrétaz, S. Lehéricy, H. Benali, and B. E. Benkelfat, L'analyse de La Voix Comme Outil de Diagnostic Précoce de La Maladie de Parkinson : Etat de l'art, CORESA 2016 : 18 e Edition COmpressions et REprésentation Des Signaux Audiovisuels, pp.113-134, 2016.

?. L. Jeancolas, G. Mangone, J. C. Corvol, M. Vidailhet, S. Lehéricy et al., Parkinson's Disease Detection at an Early Stage Using Voice, Presented in 2 nd International Conference on Neurovascular & Neurodegenerative Disease (NVND) 2019

?. L. Jeancolas, N. Villain, R. Gaurav, D. Petrovska-delacrétaz, B. E. Benkelfat et al., Voice Analysis in Early Parkinson's Disease and Correlation with Neuroimaging, Presented in 25 th Annual Meeting of Organization for Human Brain Mapping (OHBM) 2019

?. L. Jeancolas, D. Petrovska-delacrétaz, H. Benali, and B. E. Benkelfat, Analyse de La Voix Au Stade Débutant de La Maladie de Parkinson et Corrélats en Neuroimagerie, Presented in 8 th Annual Meeting of Futur & Ruptures, 2019.

?. L. Jeancolas, D. Petrovska-delacrétaz, H. Benali, and B. E. Benkelfat, Diagnostic précoce de la maladie de Parkinson par l'analyse de la voix, Colloque Evry Sciences et Innovation, 2017.

?. L. Jeancolas, D. Petrovska-delacrétaz, H. Benali, and B. E. Benkelfat, Diagnostic précoce de la maladie de Parkinson par l'analyse de la voix

, Veuillez répéter les phrases suivantes après le BIP puis terminez en tapant 1 : Tu as appris la nouvelle ? BIP Tu as bien raison ! BIP C'est pas possible ! BIP Comment il s'appelle déjà ? BIP Tu sais ce qu'il est devenu ? BIP Il n'aurait jamais du faireça ! BIP Les chiens aiment courir après les ballons. BIP Un carré est un rectangle particulier. BIP

, Maintenant en respirant quand vous voulez, veuillez répéter la syllabe /pa/ en suivant le rythme que vous allez entendre dans l'exemple, et ce pendant 30 sec. Un message sonore vous indiquera quand cela fera 30s. Ex : pa pa pa . C'està vous, L'enregistrement commencera au 1er bip et un message sonore vous indiquera quand cela fera 1min. C'està vous

;. .. Ex-pa-kou-pa-kou-.-c'està-vous and . Bip, Si durant cette cession vous avez utilisé desécouteurs merci de nous le préciser en commentaire. Sinon nous vous disonsà bientôt. Au revoir." . . . s'ils appellentà partir d'un autre téléphone que celui qu'ils ont renseigné : "Bonjour, nous n'avons pas reconnu votre numéro de téléphone. Si vous appelez pour un enregistrement mensuel de la voix dans le cadre du protocole ICEBERG, merci de nous appeler a partir du numéro que vous nous avez donné, à répéter après le BIP . Quand vous aurez fini tapez 1

M. Bonjour and . De, Vous avez 3 joursà partir de maintenant pour appeler au moment qui vous convient le mieux. La durée de l'appel sera d'environ 15 min. A tout moment pour réécouter une consigne ou refaire la tâche en cours vous pouvez taper 0. Généralement il vous sera demandé de taper 1 pour passerà la tâche suivante, sauf pour les dernières tâches où la fin sera précisée par un message sonore