Geometrical parameter combinations that correlate with early interaural cross-correlation coefficients in a performance hall

Cheung, L. Y.; Tang, S. K.

Abstract

The previous binaural data of the authors measured inside two multi-purpose performance halls are re-analyzed using regression in this study. It is done in an attempt to establish a framework that can improve the prediction of early interaural cross-correlation coefficients (IACCs), but with as little measurement effort and parameters as possible. The results show that regression models consist of linear combinations of polynomials of geometrical parameters, when used together with the measurement schemes suggested previously by the authors, are sufficient for predicting the IACCs to within engineering tolerance. The predictions are better than those obtained previously by the neural network approach of the authors. The relative importance of the geometrical parameters in the prediction of IACCs is also investigated.

Citation

Cheung, L. Y., & Tang, S. K. (2016). Geometrical parameter combinations that correlate with early interaural cross-correlation coefficients in a performance hall. The Journal of the Acoustical Society of America, 139(5), 2741-2753. https://doi.org/10.1121/1.4948995

• Journal Article Type: Article
• Acceptance Date: Apr 27, 2016
• Online Publication Date: May 16, 2016
• Publication Date: May 1, 2016
• Deposit Date: Jul 11, 2022
• Journal: Journal of the Acoustical Society of America
• Print ISSN: 0001-4966
• Publisher: Acoustical Society of America
• Peer Reviewed: Peer Reviewed
• Volume: 139
• Issue: 5
• Pages: 2741-2753
• DOI: https://doi.org/10.1121/1.4948995
• Public URL: https://hull-repository.worktribe.com/output/4015837