On the Impact of Localization Errors on HRTF-based Robust Least-Squares Beamforming
This addresses robustness issues in beamforming for audio processing, but it is incremental as it builds on existing methods.
The paper analyzed the robustness of an HRTF-based robust least-squares beamformer against localization errors, finding that these errors degrade performance, with comparisons to free-field designs showing impacts on signal measures and word error rates.
In this work, a recently proposed Head-Related Transfer Function (HRTF)-based Robust Least-Squares Frequency-Invariant (RLSFI) beamformer design is analyzed with respect to its robustness against localization errors, which lead to a mismatch between the HRTFs corresponding to the actual target source position and the HRTFs which have been used for the beamformer design. The impact of this mismatch on the performance of the HRTF-based RLSFI beamformer is evaluated, including a comparison to the free-field-based beamformer design, using signal-based measures and word error rates for an off-the-shelf speech recognizer.