Sound Quality Evaluation of Acoustical Environments with Multiple Sources

Invited paper

Sabrina Skoda

FH Düsseldorf

Wednesday 3 june, 2015, 14:20 - 14:40

0.2 Berlin (90)

Sonic environments in everyday life are usually composed of multiple sound sources with different acoustical characteristics. Thereby, spectral and temporal masking effects occurring when multiple sounds interfere with each other, as well as visual stimuli and cognitive processes like attention focusing influence our perception and evaluation of the acoustical environment. In order to explain annoyance reactions to combined noise sources, various models based on the summation of loudness or sound pressure levels have been developed recently. However, these models are limited, as natural sounds, for example, can also have a beneficial effect in noisy environments, although they represent additional sound sources. Against this background, predicting human evaluation of complex acoustical environments still poses a challenge. To focus on fundamental evaluation mechanisms, we conducted two listening experiments under laboratory conditions, where we investigated how the pleasantness ratings of singular sounds affect the overall evaluation of their respective combinations. In the course of the first study, participants had to evaluate technical and natural sounds commonly occurring in suburban areas. Based on the results, a linear regression model was proposed, which explains well the overall pleasantness evaluation of two combined stationary sounds based on the weighted sum of the singular ratings and their interaction. In this model, unpleasant sounds receive a greater weight compared to pleasant ones, which presumably is due to negativity dominance and partial masking effects. A second listening study was performed with the same test design as in the first experiment, but with three combined sounds. The results from the second experiment were used to validate the existing regression model. An extended model predicting overall pleasantness evaluations based on singular ratings helps establishing a perception-oriented classification of complex acoustical environments and the calculation of noise surcharges.

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