CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Robust Personal Audio Geometry Optimization in the SVD-Based Modal Domain
Authors
I Burnett
P Coleman
+4 more
X Qiu
M Wu
J Yang
Q Zhu
Publication date
27 December 2018
Publisher
'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Cite
Abstract
© 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
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Crossref
See this paper in CORE
Go to the repository landing page
Download from data provider
Last time updated on 11/12/2020
Surrey Research Insight
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:surrey.eprints-hosting.org...
Last time updated on 16/05/2021
OPUS - University of Technology Sydney
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:opus.lib.uts.edu.au:10453/...
Last time updated on 18/10/2019
University of Surrey
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:alma.44SUR_INST:1113940967...
Last time updated on 01/08/2022