FOR 2457:  Acoustic Sensor Networks

• Subject Area: Computer Science, Systems and Electrical Engineering
• Term: since 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 282835863

In daily life, we are surrounded by a multitude of noises and other acoustic events. Nevertheless we are able to effortlessly converse in such an environment, retrieve a desired voice while disregarding others, or draw conclusions about the composition of the environment and activities therein, given the observed sound scene. A technical system with similar capabilities would findnumerous applications in fields as diverse as ambient assisted living, personal communications, and surveillance. With the continuously decreasing cost of acoustic sensors and the pervasiveness of wireless networks and mobile devices, the technological infrastructure of wireless acoustic sensor networks is available, and the bottleneck for unleashing new applications is clearly on thealgorithmic side.This Research Unit aims at rendering acoustic signal processing and classification over acoustic sensor networks more ’intelligent’, more adaptive to the variability of acoustic environments and sensor configurations, less dependent on supervision, and at the same time more trustworthy for the users. This will pave the way for a new array of applications which combine advanced acousticsignal processing with semantic analysis of audio. The project objectives will be achieved by adopting a three-layer approach treating communication and synchronization aspects on the lower, signal extraction and enhancement on the middle, and acoustic scene classification and interpretation on the upper layer. We aim at applying a consistent methodology for optimization acrossthese layers and a unification of advanced statistical signal processing with Bayesian learning and other machine learning techniques. Thus, the project is dedicated to pioneering work towards a generic and versatile framework for the integration of acoustic sensor networks in several classes of state-of-the-art and emerging applications.

• DFG Programme: Research Units

Projects

• Acoustic Signal Extraction and Enhancement (Applicant Kellermann, Walter )
• Coordination Funds (Applicant Häb-Umbach, Reinhold )
• Distributed Acoustic Signal Processing over Wireless Sensor Networks (Applicants Karl, Holger ;  Schmalenströer, Jörg )
• Privacy-preserving Audio Features for Clustering and Classification in Acoustic Sensor Networks (Applicant Martin, Rainer )
• Sound recognition with limited supervision over sensor networks (Applicant Häb-Umbach, Reinhold )
• Time-Synchronization for Coherent Digital Signal Processing in Wireless Acoustic Sensor Networks (Applicant Enzner, Gerald )

• Spokesperson: Professor Dr.-Ing. Reinhold Häb-Umbach