A noise-aware methodology for a Mobile Voice Screening application

Dysphonia is a qualitative and quantitative alteration of the voice due to a structural or functional modification of one or more organs involved in voice production. Voice disorders are prevalent in certain working categories, particularly those of teachers, singers and actors. It is possible to evaluate the state of health of a voice through the acoustic analysis of the speech signal. This provides information about the presence of dysphonia by calculating specific parameters, such as the Fundamental Frequency (F0). In this paper we present a methodology to estimate F0 embedded in an m-health application, able to perform a simple and fast voice screening. The app acquires a user's vocal signal, and then elaborates and analyses it, distinguishing between a pathological and a healthy voice. Unfortunately, during the signal acquisition a noise can alter the F0's estimation, introducing possible errors in the acoustic analysis and therefore increasing the potential number of false-positive diagnoses of voice disorders. For this reason, the methodology presented is also able to reduce the incidence of any additional noise accidentally added during the user's vocal signal acquisition.