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

Qiaoxi Zhu*, Philip Coleman, Xiaojun Qiu, Ming Wu, Jun Yang, Ian Burnett

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number8590807
Pages (from-to)610-620
Number of pages11
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume27
Issue number3
DOIs
Publication statusPublished - Mar 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

ASJC Scopus Subject Areas

  • Computer Science (miscellaneous)
  • Acoustics and Ultrasonics
  • Computational Mathematics
  • Electrical and Electronic Engineering

Keywords

  • robustness
  • sound zones
  • Spatial audio

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