The random-incidence absorption coefficient is measured in a reverberation room as per ISO354:2003 (2003), assuming a diffuse and isotropic sound field. However, reproducibility issues across different laboratories suggest that the assumption of isotropy does not hold in practice.

This dissertation presents a novel experimental method for capturing and analyzing the directional characteristics of energy decay in reverberation rooms. The method involves decomposing the sound field into plane waves using microphone arrays. Using Schroeder integration, the newly introduced directional energy decay curve (DEDC) is calculated on the time dependent angular plane waves density function. The DEDC is decomposed into spherical harmonics, which are used to formulate time-dependent estimators for isotropy and axial symmetry. The estimators are formulated by leverage the symmetry relationships of spherical harmonics and offer high temporal and angular resolution. The DEDC framework further enables the analysis of directionally non-uniform damping of the sound field. An inverse problem is formulated using the DEDC framework and a stochastic model for directionally dependent energy decay. Variational inference is utilized to identify the model parameters and provide uncertainty measures. Experimental results obtained in a reverberation room in four configurations are presented. These configurations include the room with and without a highly absorptive glass wool specimen, and both configurations additionally with and without panel diffusers. The findings reveal non-isotropic sound fields, particularly in the presence of the absorbing specimen. It is shown that sound field isotropy varies over time, decreasing in configurations for which non-uniform distributions of damping are identified.

Finally, the relationship between the symmetry quantification results and the errors in the random-incidence absorption coefficient is explored using a statistic model. A combined factor analysis and linear regression model reveals a statistically significant relationship between the estimators and the absorption coefficient error. The results further suggest that the model is capable of correcting the measured absorption coefficient if data from multiple laboratories are available.

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