Machine Learning in Acoustics
The use of machine learning (ML) in acoustics has received much attention in the last decade. ML is unique in that it can be applied to all areas of acoustics. ML has transformative potentials as it can extract statistically based new information about events observed in acoustic data. Acoustic data provide scientific and engineering insight ranging from biology and communications to ocean and Earth science. This special issue included 65 papers, illustrating the very diverse applications of ML in acoustics.
Guest Editors: Zoi-Heleni Michalopoulou, Peter Gerstoft, Bozena Kostek, Marie A. Roch
Image credit: Figure 1 from "Introduction to the special issue on machine learning in acoustics," J. Acoust. Soc. Am. 150, 3204 (2021).