Acoustic Analysis of Voice Disorders from Clinical Perspective

Abstract

Voice disorders are caused due to abnormality in the laryngeal system. The signs and symptoms newlineof voice disorder may include: abnormal pitch (too high pitch, too low pitch, pitch breaks), reduction newlinein loudness, degradation of individual s voice quality (breathy, rough, and strained voice quality), loss newlineof voice and so on. Instrumental assessment, auditory-perceptual assessment and objective assessment newlineare most widely used methods for diagnosing the voice disorders. Instrumental assessment methods newlineoften involve the use of laryngoscopes and stroboscopes, but these procedures can be expensive and newlinepainful. Auditory-perceptual methods used by Speech-Language Pathologists (SLPs) is considered as newlinea gold standard for detecting voice disorder. The decisions taken in the subjective intelligibility test newlinevary with experience of SLPs, type of scale used, and also depend on the examiner s experience. To newlineaddress these limitations, objective or automatic assessment methods have been extensively explored in newlinethe literature. These approaches extract acoustic features from speech signals, offering reliable, costeffective, newlineand repeatable assessments. Objective assessment methods have potential to be used as a newlinepre-diagnostic measure for voice disorder assessment by SLPs. This thesis primarily focuses on the newlineobjective or automatic assessment methods of voice disorders. newlineVarious objective assessment methods for the automatic detection of voice disorders have been explored newlinein the literature. These methods aim to detect the presence or absence of voice disorders, as well newlineas assess their severity ratings. However, clinical assessment of voice disorders relies on considering newlinethe underlying etiological diagnosis. Therefore, this study proposes a clinical approach to assess voice newlinedisorders. Along with the detection which was explored in the literature, this thesis explored an objective newlineassessment method which can automatically identify the cause of voice disorders based on the newlineacoustic features extracted from the speech signal. The resulting sp