Hendrik Barfuss
Papers
8
Total Citations
174
H-Index
6
About
Hendrik Barfuss is a leading researcher in acoustic signal processing, with a primary focus on robot audition and acoustic source localization. His work addresses the fundamental challenge of enabling humanoid robots to hear and interpret sound in complex, dynamic environments—a critical capability for natural human-robot communication. Barfuss’s major contributions center on developing adaptive microphone array topologies and robust beamforming techniques that account for the acoustic shadowing effects of a robot’s own head. He pioneered the use of Head-Related Transfer Functions (HRTFs) to design frequency-invariant beamformers, allowing robots to maintain consistent spatial filtering performance even as they move. His most cited work, "The LOCATA Challenge Data Corpus" (103 citations), provided a standardized benchmark that has become essential for evaluating source localization and tracking algorithms across the field. Barfuss also introduced dynamic acoustic sensing methods that enable robots to process sound while in motion, rather than requiring them to stop—a practical breakthrough for real-world deployment. His research has been published in top venues including the IEEE/ACM Transactions on Audio, Speech, and Language Processing, and he has been an active contributor to the international community on acoustic signal enhancement for human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1The LOCATA Challenge Data Corpus for Acoustic Source Localization and Tracking103 citations · 2018
- 2Challenges in Acoustic Signal Enhancement for Human-Robot Communication22 citations · 2014
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- 4HRTF-based robust least-squares frequency-invariant beamforming13 citations · 2015
- 5Enhanced robot audition by dynamic acoustic sensing in moving humanoids10 citations · 2015
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