Abstract:
Computer Audition – the analysis and synthesis of speech, music, and sound – is one of the key pillars in Artificial Intelligence. The rise of large foundation models has profoundly reshaped the landscape of AI, including Computer Audition. Like in other domains, these models exhibit emergent behaviours, showcasing unprecedented potential in audio processing. In this talk, we will explore the latest cutting-edge approaches to Computer Audition, examining how the new era of foundation models is transforming the field. To highlight the impact and capabilities of the upcoming generation of Computer Audition models, a range of diverse use cases will be demonstrated. We will also introduce a new, richly attributed representation of audio, embodying both states and traits in depth and width that is set to revolutionize computational processing of audio. Finally, we will dive into novel algorithms that address the unique challenges of training and deploying these advanced models. This talk will guide you through the exciting possibilities and opportunities emerging in this field, while also shedding light on the potential pitfalls to navigate as we move forward. In summary, the emergence of foundation models in Computer Audition heralds a new age of intelligent audio processing. With these advancements, we stand at the cusp of remarkable breakthroughs – where machines will interact with audio in ways we are only beginning to imagine.
Biography:
Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany where he is Full Professor and Chair of Health Informatics. He is also Full Professor of Artificial Intelligence and the Head of GLAM at Imperial College London/UK, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, Core Member in the Munich Data Science Institute (MDSI), Principal Investigator in the Munich Center for Machine Learning (MCML), Fellow of the Imperial Data Science Institute, and permanent Honorable Dean at TJNU/China and Visiting Professor at HIT/China amongst other Professorships and Affiliations. Previous stays include Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, independent research leader within the Alan Turing Institute, Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the ACM, Fellow of the IEEE and Golden Core Awardee of the IEEE Computer Society, Fellow of the BCS, Fellow of the ELLIS, Fellow of the ISCA, Fellow and President-Emeritus of the AAAC, and Elected Full Member Sigma Xi. He (co-)authored 1,500+ publications (60,000+ citations, h-index >110), is Field Chief Editor of Frontiers in Digital Health, Editor in Chief of AI Open and was Editor in Chief of the IEEE Transactions on Affective Computing amongst manifold further commitments and service to the community. His 50+ awards include having been honoured as one of 40 extraordinary scientists under the age of 40 by the WEF in 2015. Currently, he was awarded ACM Distinguished Speaker for the term 2024-2027 and IEEE Signal Processing Society Distinguished Lecturer 2024. He served as consultant of companies such as Barclays, Huawei, or Samsung. Schuller counts more than 300 public press appearances including in the Guardian, Newsweek, Scientific American, Times, or UK Daily Mail, and international podcast, radio, and television contributions such as in MIT Technology Review, “The World” and “The Why”.
