BioVoice: a multipurpose tool for voice analysis

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis

Testing software tools with synthesized deviant voices for medicolegal assessment of occupational dysphonia

The measure of acoustic parameters related to dysphonia has long been one of the main research challenges in voice analysis. When the origin of the voice disorder is occupational, the medico-legal and insurance aspects must be considered, involving, when relevant, the definition of a percentage of physical impairment (usually 1-10% according to the guidelines). An objective aid capable of quantifying these levels is desirable for assisting the medico-legal expert. Vocal fold nodules in voice professionals are mentioned in the European List of Occupational Diseases. Generally, such voices are slightly to moderately deviant, and mainly characterized by audible air escape (breathiness), due to insufficient vocal fold closure. Mild amounts of jitter may also be present. No studies have been published so far testing the ability of software tools to discriminate levels of added noise in signals when the amount of noise is exactly known. In the present study, four program tools (BioVoice, PRAAT, MDVP and AMPEX) are tested on realistic synthesized voice signals corrupted by 4 slightly increasing levels of jitter and 10 levels of additive noise close to the degree of dysphonia occurring in real patients with vocal fold nodules. The results show that the four tools are able to correctly estimate both jitter and noise levels. Specifically for noise, in some cases the agreement is close to 100%. Thus they could be of help to clinicians in determining the level of impairment to quantify compensation in patients affected by an occupational voice disorder. © 2014 Elsevier Ltd.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Non Invasive Tools for Early Detection of Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic