A principal components model of soundscape perception

TLDR

A model is needed to identify underlying dimensions of soundscape perception to guide measurement and improvement of soundscape quality. The study aimed to develop a model of soundscape perception and to identify the basic dimensions and measurement scales needed to promote high‑quality soundscapes. The authors conducted a listening experiment with 100 participants rating 50 urban outdoor soundscape recordings on 116 attribute scales, then correlated the resulting principal‑component scores with physical soundscape properties such as dominant sound categories and acoustic variables. Principal‑components analysis identified three dimensions—Pleasantness, Eventfulness, and Familiarity—explaining 50%, 18%, and 6% of variance, with technological sounds linked to unpleasantness, natural sounds to pleasantness, and human sounds to eventfulness, relationships that persisted after controlling for loudness, thereby offering a framework for future soundscape research and practice.

Abstract

There is a need for a model that identifies underlying dimensions of soundscape perception, and which may guide measurement and improvement of soundscape quality. With the purpose to develop such a model, a listening experiment was conducted. One hundred listeners measured 50 excerpts of binaural recordings of urban outdoor soundscapes on 116 attribute scales. The average attribute scale values were subjected to principal components analysis, resulting in three components: Pleasantness, eventfulness, and familiarity, explaining 50, 18 and 6% of the total variance, respectively. The principal-component scores were correlated with physical soundscape properties, including categories of dominant sounds and acoustic variables. Soundscape excerpts dominated by technological sounds were found to be unpleasant, whereas soundscape excerpts dominated by natural sounds were pleasant, and soundscape excerpts dominated by human sounds were eventful. These relationships remained after controlling for the overall soundscape loudness (Zwicker’s N10), which shows that ‘informational’ properties are substantial contributors to the perception of soundscape. The proposed principal components model provides a framework for future soundscape research and practice. In particular, it suggests which basic dimensions are necessary to measure, how to measure them by a defined set of attribute scales, and how to promote high-quality soundscapes.