Monitoring Applications with Sound Data: A Systematic Literature Review on Sound Classification with Transfer Learning
Fabian Klärer, Jonas Werner, Marco Klaiber, Felix Gerschner, Manfred Rössle · Procedia Computer Science · 2024
Audio Classification using Machine Learning (ML) techniques has gained significant importance in various domains such as speech recognition, music Classification, and environmental sound analysis. Especially in combination with Transfer Learning (TL), this is a promising technique, which is why we conduct a Systematic Literature Review (SLR) on approaches in this domain, with a focus on sound Classification for monitoring tasks, which differ significantly from speech and music Classification. Furthermore, we provide an overview of TL techniques and applications, considering different methods due to the inherent characteristics of acoustic sound data. Based on our SLR, the advantages and disadvantages of the approaches are highlighted, and further research needs are identified.