Abstract

Imagine you are standing on a street corner in a city. Close your eyes: what do you hear? Perhaps some cars and busses driving on the road, footsteps of people on the pavement, beeps from a pedestrian crossing, and the hubbub of talking shoppers. You can do the same in a kitchen as someone is making breakfast, or as you are travelling in a vehicle. Now, following the success of AI and machine learning technologies for speech and image recognition, we are beginning to build computer systems to automatically recognize real-world sound scenes and events. In this talk, we will explore some of the work going on in this rapidly expanding research area, and discuss some of the potential applications emerging for sound recognition, from assisted living to environmental noise and sound archives. We will also outline how we are adopting participatory methods to help us realise the potential benefit of sound sensing to society and the economy.

Bio: Prof. Mark Plumbley is Professor of Signal Processing at the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey, in Guildford, UK. He is an expert on analysis and processing of audio, using a wide range of signal processing and machine learning methods. He led the first international data challenge on Detection and Classification of Acoustic Scenes and Events (DCASE), and is a co-editor of the book “Computational Analysis of Sound Scenes and Events” (Springer, 2018). He currently holds a 5-year EPSRC Fellowship “AI for Sound” on automatic recognition of everyday sounds. He is a Member of the IEEE Signal Processing Society Technical Committee on Audio and Acoustic Signal Processing, and a Fellow of the IET and IEEE .