Data relating to the AES conference paper "A framework for intelligent metadata adaptation in object-based audio"
datasetposted on 04.04.2019 by James Stephen Woodcock, Jon Francombe, Andreas Franck, Philip Coleman, Richard James Hughes, Hansung Kim, Qingju Liu, Dylan Menzies, Marcos Simon Galvez, Yan Tang, Tim Brookes, William Jonathan Davies, Bruno Miguel Fazenda, Russell Mason, Trevor John Cox, Filippo Maria Fazi, Phillip J.B. Jackson, Chris Pike, Adrian Hilton
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
This archive contains the data and analysis scripts to reproduce the results in:
Woodcock, J., Francombe, J., Franck, A., et al. (2018, July). A framework for intelligent metadata adaptation in object-based audio. In Audio Engineering Society Conference: 2018 AES International Conference on Spatial Reproduction-Aesthetics and Science. Audio Engineering Society.
The MATLAB scripts ./analysis.m runs all of the comparison of the experimental data and proposed rendering rules presented in the paper.