Invited Research Seminar

Machine Listening in Urban/Bio-Acoustic Environments & tools for sustainable MIR research by Justin Salamon.

Abstract

Internet of Things (IoT) sensor networks, and particularly acoustic sensor networks, open up new opportunities in large-scale, data-driven analyses of acoustic environments. Examples include (but are not limited to) monitoring noise sources in urban environments or monitoring the migration of bird species based on their vocalizations. In both cases, it is necessary to identify and classify specific sound events in an audio signal based on their source, be it jackhammers and car honks or different species of migrating warblers. In this talk I'll present our work on machine listening algorithms for source identification in acoustic environments as part of the Sounds of New York City (SONYC) and BirdVox projects. Finally, I will also give a brief overview of the tools/resources we have been developing for sustainable MIR research including JAMS, mir_eval, Scaper and Massage.

Biography

Justin Salamon is a Senior Research Scientist at New York University's Music and Audio Research Lab (MARL) and Center for Urban Science and Progress (CUSP). He obtained a B.A. (Hons.) in Computer Science from the University of Cambridge, UK, in 2007, and an M.Sc. (2008) and Ph.D. (2013) in Computer Science from the Music Technology Group (MTG) of Pompeu Fabra University (UPF), Barcelona, Spain, specializing in sound and music computing. He was a visiting researcher at the Sound Analysis-Synthesis research team of the Institut de Recherche et Coordination Acoustique/Musique (IRCAM), Paris, France. His research interests include digital signal processing, machine learning and data mining, with applications to machine listening, music information retrieval, bioacoustics and environmental sound analysis. For further information and a full list of publications please see: www.justinsalamon.com