Summary of “Statistical learning and data science techniques in acoustics research”

Increases in computational capabilities have made statistical learning and data science techniques more accessible to researchers. This paper summarizes research presented in two special sessions, one each at the Spring 2016 meeting in Salt Lake City, UT and the Spring 2017 meeting in Boston, MA. The sessions were cosponsored by the Noise and Signal Processing Technical Committees. The speakers represent industry, academia, and government institutions in the United States, France, England, and the Netherlands. Presentation topics covered a variety of acoustic disciplines with a focus on machine learning techniques, Bayesian techniques, and advanced statistical models.