Pathological voice discrimination based on entropy measurements

Digital signal processing techniques have been used to analyze vocal disorders caused by laryngeal pathologies. Laryngoscopical exams commonly used for detection of these diseases are invasive methods that cause discomfort to the patients. Because of its noninvasive nature, acoustical analysis of the temporal and spectral features of the voice signal can be used as an auxiliary technique in laringoscopical exams. This analysis may be applied for detection of vocal diseases and the evaluation of the vocal quality of patients subjected to surgical processes or medical treatments in the vocal folds. This work aims at investigating the behavior of entropy measures in disordered voices influenced by the presence of pathologies in the vocal folds. For this purpose, the Shannon entropy and the relative entropy are implemented, and their behavior for normal and pathological voices affected by vocal fold edemas is observed. The measurement of the entropy efficiency in discriminating between normal and pathological voices is obtained.