HRTF-based two-dimensional robust least-squares frequency-invariant beamformer design for robot audition
This work addresses robot audition by improving sound localization and processing, but it is incremental as it builds on prior one-dimensional HRTF-based designs.
The paper tackled the problem of designing a robust beamformer for robot audition that controls the response across the entire 3D sound field, using a two-dimensional HRTF-based approach, and showed effectiveness compared to a previous one-dimensional method.
In this work, we propose a two-dimensional Head-Related Transfer Function (HRTF)-based robust beamformer design for robot audition, which allows for explicit control of the beamformer response for the entire three-dimensional sound field surrounding a humanoid robot. We evaluate the proposed method by means of both signal-independent and signal-dependent measures in a robot audition scenario. Our results confirm the effectiveness of the proposed two-dimensional HRTF-based beamformer design, compared to our previously published one-dimensional HRTF-based beamformer design, which was carried out for a fixed elevation angle only.