HRTF-Based Robust Least-Squares Frequency-Invariant Polynomial Beamforming

H. Barfuss, M. Mueglich and W. Kellermann (FAU Erlangen-Nuremberg)
Intl. Workshop on Acoustic Signal Enhancement (IWAENC), Xi’an, China, Sept. 13-16, 2016
[showhide type=”Abstract”]Abstract: In this work, we propose a robust Head-Related Transfer Function (HRTF)-based polynomial beamformer design which accounts for the influence of a humanoid robot’s head on the sound field. In addition, it allows for a flexible steering of our previously proposed robust HRTF-based beamformer design. We evaluate the HRTF-based polynomial beamformer design and compare it to the original HRTF-based beamformer design by means of signal-independent measures as well as word error rates of an off-the-shelf speech recognition system. Our results confirm the effectiveness of the polynomial beamformer design, which makes it a promising approach to robust beamforming for robot audition.[/showhide]
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Paper: Paper_IWAENC_2016_FAU_HB