Title: Current Challenges in Multichannel Acoustic Signal Processing for Natural Human/Machine Interfaces
Abstract: In recent years, the tremendous progress in acoustic human/machine interaction manifested itself in products like Amazon Echo and is often only attributed to progress in machine learning algorithms simply exploiting large amounts of data. In parallel, however, also model-based signal processing algorithms developed to previously inconceivable performance and often contribute decisively to the overall success. Especially in multichannel acoustic signal processing, e.g., the linear models for acoustic wavefields provide a reliable basis for numerous efficient techniques exploiting spatial diversity for the fundamental problems at the acoustic human/machine interface: capturing undistorted desired signals and reproducing immersive sound fields. For natural interfaces where the human speaker or listener should not need to touch or wear any gear, this implies as fundamental challenges for multichannel acoustic signal processing: acoustic feedback from loudspeakers to microphones, noise and interfering sources, and reverberation in enclosures.
In this talk, we will shortly review the fundamental problems and then highlight some recent advances for massive multichannel reproduction, signal extraction, source localization, and dereverberation, and thereby point to applications in immersive reproduction, hearing aids, smartphones, robot audition, and acoustic sensor networks. Finally, we will also outline promising avenues for future research.
Short Bio: Walter Kellermann is a professor for communications at the University of Erlangen-Nuremberg, Germany, since 1999. He received the Dipl.-Ing. (univ.) degree in Electrical Engineering from the University of Erlangen-Nuremberg, in 1983, and the Dr.-Ing. degree from the Technical University Darmstadt, Germany, in 1988. From 1989 to 1990, he was a postdoctoral Member of Technical Staff at AT&T Bell Laboratories, Murray Hill, NJ. In 1990, he joined Philips Kommunikations Industrie, Nuremberg, Germany, to work on hands-free communication in cars. From 1993 to 1999, he was a Professor at the Fachhochschule Regensburg, where he also became Director of the Institute of Applied Research in 1997. In 1999, he cofounded DSP Solutions, a consulting firm in digital signal processing, and he joined the University Erlangen-Nuremberg as a Professor and Head of the Audio Research Laboratory. He authored or coauthored 21 book chapters, 300+ refereed papers in journals and conference proceedings, as well as 70+ patents, and is a co-recipient of ten best paper awards. His current research interests include speech signal processing, array signal processing, adaptive filtering, and its applications to acoustic human–machine interfaces. Dr. Kellermann served as an Associate Editor and Guest Editor to various journals, including the IEEE Transactions on Speech and Audio Processing from 2000 to 2004, the IEEE Signal Processing Magazine in 2015, and presently serves as Associate Editor to the EURASIP Journal on Applied Signal Processing. He was the General Chair of seven mostly IEEE-sponsored workshops and conferences. He served as a Distinguished Lecturer of the IEEE Signal Processing Society (SPS) from 2007 to 2008. He was the Chair of the IEEE SPS Technical Committee for Audio and Acoustic Signal Processing from 2008 to 2010, a Member of the IEEE James L. Flanagan Award Committee from 2011 to 2014, a Member of the SPS Board of Governors (2013-2015), and is currently Vice President Technical Directions of the IEEE Signal Processing Society (2016-2018). He was awarded the Julius von Haast Fellowship by the Royal Society of New Zealand in 2012 and the Group Technical Achievement Award of the European Association for Signal Processing (EURASIP) in 2015. In 2016, he was a Visiting Fellow at Australian National University, Canberra, Australia. He is an IEEE Fellow.