Robust Personal Audio Geometry Optimization in the SVD-Based Modal Domain

Publication Type:
Journal Article
Citation:
IEEE/ACM Transactions on Audio Speech and Language Processing, 2019, 27 (3), pp. 610 - 620
Issue Date:
2019-03-01
Filename Description Size
T-ASL-06836-2018.R2_manuscript.pdfAccepted Manuscript Version1.35 MB
Adobe PDF
Full metadata record
© 2014 IEEE. Personal audio generates sound zones in a shared space to provide private and personalized listening experiences with minimized interference between consumers. Regularization has been commonly used to increase the robustness of such systems against potential perturbations in the sound reproduction. However, the performance is limited by the system geometry such as the number and location of the loudspeakers and controlled zones. This paper proposes a geometry optimization method to find the most geometrically robust approach for personal audio amongst all available candidate system placements. The proposed method aims to approach the most 'natural' sound reproduction so that the solo control of the listening zone coincidently accompanies the preferred quiet zone. Being formulated in the SVD-based modal domain, the method is demonstrated by applications in three typical personal audio optimizations, i.e., the acoustic contrast control, the pressure matching, and the planarity control. Simulation results show that the proposed method can obtain the system geometry with better avoidance of 'occlusion,' improved robustness to regularization, and improved broadband equalization.
Please use this identifier to cite or link to this item: