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, rustling and clonks from shopping bags and boxes, 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 tackle this challenging task: 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 touch on some of the key issues for the future, including ensuring privacy around sound sensors. We will discuss some of the potential applications emerging for sound recognition, from home security and assisted living to industrial condition monitoring and assessing traffic noise. We will close with some pointers to more information about this exciting future technology.
Speaker: Mark Plumbley is Professor of Signal Processing at the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey
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 and music, 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 2013), and hosted the DCASE 2018 Workshop in Woking, Surrey. He currently leads the EPSRC-funded project “Making Sense of Sounds” on automatic recognition of everyday sounds, and he is a co-editor of the recent book on “Computational Analysis of Sound Scenes and Events” (Springer, 2018).
19:00 Talk starts
20.30 Event close
Complimentary drinks and canapes will be provided.