Farshad Almasganj

Computational Analysis of Voice Disorders: Signal Processing Approaches to Non-invasive Diagnosis of Laryngeal Diseases in Patients with Pathological Speech Farshad Almasganj

The development of mathematical methods for analyzing pathological speech signals is one of the best approaches to non-invasive diagnosis of laryngeal dysfunctions in patients with vocal fold disorders. The processing of disordered voice signals is a useful technique that provides a low-cost and time-efficient clinical tool for automatic detection of neurological and physical damages to the vocal folds. The application of these methods can help speech pathologists routinely monitor the functionality of patients' speech production system and provide them with appropriate therapies, medication or treatments. Moreover, these method can help detect the early symptoms and prevent the progress of some severe types of these diseases (e.g. laryngeal cancer) by tracking changes in the acoustical parameters of a patients' voice. In this book, a variety of signal processing methods are proposed, implemented and discussed with relevance to the diagnosis of different types of laryngeal diseases. The discussed methods include classical and novel signal processing approaches to the diagnosis of laryngeal diseases with specific focus on vocal fold disorders in patients with pathological speech.