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Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson's Disease. ; This work is being funded by Grants TEC2016-77791-C4-4-R from the Ministry of Economic Affairs and Competitiveness of Spain, Teka-Park 55 02 CENIE-0348_CIE_6_E POCTEP (InterReg Programme) and 16-30805A, SIX Research Center (CZ.1.05/2.1.00/03.0072), and LO1401 from the Czech Republic Government.

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. E. Khoury , B. Vesnicer, J. Franco-Pedroso, R. Violato, Z. Boulkenafet, L.M. Mazaira Fernández, M. Díez, J. Kosmala, H. Khemiri, T. Cipr, R. Saeidi, M. Gunther, J. Zganec-Gros, R. Zazo Candil, F. Simöes, M. Bengherabi, A. Álvarez Marquina, M. Penagarikano, A. Abad, M. Boulayemen, P. Schwarz,, D. Van Leeuwen, J. González-Domínguez, M. Uliani Neto, E. Boutellaa, P. Gómez Vilda, A. Varona, D. Petrovska-Delacretaz, P. Matejka, J. González-Rodríguez, T. Pereira, F. Harizi, L. J. Rodríguez-Fuentes, L. El Shafey, M. Angeloni, G. Bordel, G. Chollet, S. Marcel, "The 2013 speaker recognition evaluation in mobile environment" in International Conference on Biometrics (ICB), Madrid (Spain), 2013, 1-8 ; This paper evaluates the performance of the twelve primary systems submitted to the evaluation on speaker verification in the context of a mobile environment using the MOBIO database. The mobile environment provides a challenging and realistic test-bed for current state-of-the-art speaker verification techniques. Results in terms of equal error rate (EER), half total error rate (HTER) and detection error trade-off (DET) confirm that the best performing systems are based on total variability modeling, and are the fusion of several sub-systems. Nevertheless, the good old UBM-GMM based systems are still competitive. The results also show that the use of additional data for training as well as gender-dependent features can be helpful. ; This evaluation was supported by the European Union under the project BEAT contract no. FP7-284989 , as well as the Swiss National Science Foundation under the LOBI project.