TY - GEN
T1 - A framework for intelligent metadata adaptation in object-based audio
AU - Woodcock, James
AU - Francombe, Jon
AU - Franck, Andreas
AU - Coleman, Philip
AU - Hughes, Richard
AU - Kim, Hansung
AU - Liu, Qingju
AU - Menzies, Dylan
AU - Simón Gálvez, Marcos F.
AU - Tang, Yan
AU - Brookes, Tim
AU - Davies, William J.
AU - Fazenda, Bruno M.
AU - Mason, Russell
AU - Cox, Trevor J.
AU - Fazi, Filippo Maria
AU - Jackson, Philip J.B.
AU - Pike, Chris
AU - Hilton, Adrian
N1 - Funding Information:
This work was supported by the EPSRC Programme Grant S3A: Future Spatial Audio for an Immersive Listener Experience at Home (EP/L000539/1). The data underlying this work, along with the terms for data access, are available from http://dx.doi.org/ 10.17866/rd.salford.6050621.
Publisher Copyright:
© (2018) by the Audio Engineering Society All rights reserved.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Object-based audio can be used to customize, personalize, and optimize audio reproduction depending on the specific listening scenario. To investigate and exploit the benefits of object-based audio, a framework for intelligent metadata adaptation was developed. The framework uses detailed semantic metadata that describes the audio objects, the loudspeakers, and the room. It features an extensible software tool for real-time metadata adaptation that can incorporate knowledge derived from perceptual tests and/or feedback from perceptual meters to drive adaptation and facilitate optimal rendering. One use case for the system is demonstrated through a rule-set (derived from perceptual tests with experienced mix engineers) for automatic adaptation of object levels and positions when rendering 3D content to two-and five-channel systems.
AB - Object-based audio can be used to customize, personalize, and optimize audio reproduction depending on the specific listening scenario. To investigate and exploit the benefits of object-based audio, a framework for intelligent metadata adaptation was developed. The framework uses detailed semantic metadata that describes the audio objects, the loudspeakers, and the room. It features an extensible software tool for real-time metadata adaptation that can incorporate knowledge derived from perceptual tests and/or feedback from perceptual meters to drive adaptation and facilitate optimal rendering. One use case for the system is demonstrated through a rule-set (derived from perceptual tests with experienced mix engineers) for automatic adaptation of object levels and positions when rendering 3D content to two-and five-channel systems.
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M3 - Conference contribution
AN - SCOPUS:85060221885
T3 - Proceedings of the AES International Conference
SP - 349
EP - 359
BT - AES International Conference on Spatial Reproduction 2018
PB - Audio Engineering Society
T2 - AES International Conference on Spatial Reproduction 2018: Aesthetics and Science
Y2 - 7 August 2018 through 9 August 2018
ER -