Webinar – Robot audition, Christine Evers (Southampton)
Audio signals encapsulate a wealth of semantic information, including cues about nearby sound events and the surrounding environment. As such, sound is used in nature to communicate, to detect salient events, to navigate, and to self-localise. Audition – the ability to make sense of sounds – is therefore a fundamental prerequisite for robots. However, in practice, robots are deployed in complex, acoustic scenes that are subject to uncertainties arising from the ego-motion of the robot, as well as to ambiguities due to multiple, active sound sources.
In this talk, Dr Christine Evers will discuss her work on robot audition. Following an outline of the challenges affecting dynamic, acoustic scenes, the talk will highlight recent advances at the intersection of acoustic signal processing and machine learning, equipping robots with the ability to make sense of life in sound.
Dr. Christine Evers is a Lecturer in the School of Electronics & Computer Science at the University of Southampton. Her research focuses on Bayesian inference for machine listening.
Prior to joining the University of Southampton, Christine was the recipient of an EPSRC Fellowship to advance her work on “Acoustic Signal Processing and Scene Analysis for Socially Assistive Robots”, hosted at Imperial College London between 2017-2019. Her fellowship followed positions as a research associate on the FP7 project “Embodied Audition for Robots” at Imperial College between 2014-2016; as a senior systems engineer at Selex Electronic Systems, Edinburgh, between 2010-2014; and as a research fellow at the University of Edinburgh between 2009-2010. Christine received her PhD from the University of Edinburgh, UK, in 2010.
Christine is a Co-I on the Trustworthy Autonomous Systems Hub, and the cohort lead as well as the theme lead for ‘Embedded AI’ on the UKRI Centre for Doctoral Training in Machine Intelligence for Nano- Electronic Devices and Systems (MINDS). She is a Senior Member of the IEEE, an elected member of the IEEE Signal Processing Society Technical Committee on Audio and Acoustic Signal Processing, and serves as an associate editor of the EURASIP Journal on Audio, Speech, and Music Processing.
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Early Careers SIG Webinar Series
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