7th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 2011)

Florence, Italy
August 25-27, 2011

Voice Quality Analysis to Detect Neurological Diseases

Pedro Gómez-Vilda (1), V. Rodellar-Biarge (1), V. Nieto (1), L. M. Mazaira (1), C. Muñoz (1), M. Fernández (2), E. Toribio (2)

(1) Grupo de Informática Aplicada al Procesado de Señal e Imagen, Universidad Politécnica de Madrid, Spain
(2) ENT and Neurology Services, Hospital del Henares, Coslada, Madrid, Spain

Neurological degenerative diseases are becoming a growing concern in modern society. The successful treatment of these diseases depend greatly in early detection. Speech has been routinely used by specialists as a valuable correlate in the assessment of pathological disease. Specifically voicing can serve as a very introspective correlate for this practice. The present paper uses a methodology previously employed in organic pathology voice quality assessment to explore to what extent specific low-level correlates of neurological diseases may be established. The methodology uses voiced recordings of sustained vowels to estimate vocal fold visco-elastic parameters from inverse filtering. These parameters show to be clearly influenced by unstable neuronal spiking resulting in tremor which affects many phonation cycles. The possible modeling of tremor could be used as an index to neuro-motor problems in phonation and help in differential diagnose of the pathology at an early stage. The paper presents examples on parameter estimations from study cases of spasmodic dysphonia and Parkinson Disease. Further development of research lines on this estimation methodology is also addressed.

Index Terms. Inverse Filtering, Vocal Fold Biomechanics, Parkinson Disease, Voice Quality Assessment, Tremor

Full Paper (reprinted with permission from Firenze University Press)

Bibliographic reference.  Gómez-Vilda, Pedro / Rodellar-Biarge, V. / Nieto, V. / Mazaira, L. M. / Muñoz, C. / Fernández, M. / Toribio, E. (2011): "Voice quality analysis to detect neurological diseases", In MAVEBA-2011, 79-82.