Machine Learning for Acoustic Scene and Respiratory Sound Classification
Acoustic scene classification is an important task of a machine hearing system used for classification of general sounds in everyday environments. It aims to characterize and label the acoustic environment of an audio recording. While respiratory sounds classification is a key task on computer-aided lung sound research to support medical diagnosis. It focuses on automatic recognition of respiratory adventitious sounds or healthy and several categories of pathological lung sounds. The thesis develops machine learning methods for these application tasks.