Voice quality analysis was performed in 88 normal speakers and 157 dysphonic speakers using a device that allows simultaneous study of acoustic and aerodynamic parameters during pronunciation of a sustained /a/. We compared the results with those of voice quality grading by a jury. The Mann-Whitney test showed significant differences between the grades of dysphonia for all the parameters chosen. Comparison of results (using discriminant factorial analysis) with perceptual evaluation by a jury showed concordance in 66.1%. Based on these preliminary results, the authors conclude that their protocol overlooks some relevant voice parameters like middle-term variations. Further study will be undertaken to take into account this type of variations.

Most of the existing systems and methods for laryngeal pathology detection are characterized by a classification error. One of the basic problems is the approximation and estimation of the probability density functions of the given classes. In order to increase the accuracy of laryngeal pathology detection and to eliminate the most dangerous error--classification of a patient with laryngeal disease as a normal speaker--here an approach based on modeling of the probability density functions (pdf's) of the input vectors of the normal and pathological speakers by means of two prototype distribution maps (PDM), respectively, is proposed. The pdf of the input vectors of an unknown normal or pathological speaker is also modeled by such a prototype distribution neural map--PDM(X)--and the pathology detection is done by means of a ratio of specific similarities rather than by a direct comparison of some type of distance/similarity with a threshold. The experiments show an increased classification accuracy and that the proposed method can be used for screening the laryngeal diseases. The method is applied in a consulting system for clinical practice.

International audienceThe aim of this contribution is to propose a database model designed for the storage and accessibility of various speech disorder data including signals, clinical evaluations and patients' information. This model is the result of 15 years of experience in the management and the analysis of this type of data. We present two important French corpora of voice and speech disorders that we have been recording in hospitals in Marseilles (MTO corpus) and Aix-en-Provence (AHN corpus). The population consists of 2500 dysphonic, dysarthric and control subjects, a number of speakers which, as far as we know, constitutes currently one of the largest corpora of " pathological " speech. The originality of this data lies in the presence of physiological data (such as oral airflow or estimated sub-glottal pressure) associated with acoustic recordings. This activity led us to raise the question of how we can manage the sound, physiological and clinical data of such a large quantity of data. Consequently, we developed a database model that we present here. Recommendations and technical solutions based on MySQL, a relational database management system, are discussed