Durham School of Architectural Engineering and Construction
First Advisor
Lily M. Wang
Date of this Version
12-2016
Document Type
Article
Citation
Bliefnick, Jay. "Investigation of Subjective Perception & Objective Metrics of Acoustic Room Diffusion." 2016.
Abstract
While a variety of assessment methodologies have been proposed to quantify acoustic diffusivity within rooms, a link between these and the perception of diffusion has not been fully established. This study investigated various ways of analyzing diffusion, through both human perception and objective metrics. Numerous impulse response measurements were collected from a physical acoustics testing facility designed for diffusion research. This space featured reversible absorptive/diffusive/reflective wall panels, which allowed numerous testing configurations. One such setup investigated how changing the diffusivity of an isolated wall surface impacted diffusive room conditions. Alternatively, the effects diffuser configurations had on diffusive room conditions were also explored.
The collected room impulse response measurements were utilized in subjective trials and an objective metric analysis. In the subjective testing, room auralizations were presented to subjects in audio comparison trials to determine how well diffusive room conditions could be discerned. It was found that a significant quantity of diffusive surface area was required for the average subject to discriminate between the presented diffusive and absorptive wall conditions. Subjects were even less capable of discerning between the diffusive and reflective wall conditions presented. In addition, Male Speech was found to be more distinguishable than Violin Music, and musicians identified diffusive room conditions more effectively than non-musicians. The objective metric analysis identified the Number of Peaks as the most effective diffusive quantification methodology. Also, two metrics designed to measure reflection strengths within impulse responses were identified: Slope Ratio and the Degree of Time Series Fluctuations.
Advisor: Lily M. Wang
Comments
A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Architectural Engineering, Under the Supervision of Professor Lily M. Wang. Lincoln, Nebraska: December, 2016
Copyright 2016 Jay Michael Bliefnick