Year: 2024
Type: conference-paper
Abstract: In an attempt to cultivate standardization in soundscape reporting Brown, Kang and Gjestland offered \nan influential schema by which the acoustic environment is divided initially into indoor and outdoor environments, and within each into further categories; urban, rural, wilderness, and underwater. Within each of these, sounds are categorised with increasing levels of detail. However, this schema is offered as an organizational framework for further elaboration, rather than as an evidence-based account of semantic categories. In other soundscape categorisation research semantic differential data are used to examine how perceptually similar sounds are. However, this approach typically involves prescribing descriptive terms, taken from previous research or simply prescribed by the researcher, rather than eliciting descriptive terms and semantic categories per se. Another common method for identifying semantic categories is to perform multidimensional scaling and cluster analysis of similarity data generated by a pairwise comparison task. This approach avoids prescribing attributes with which to rate sounds; however the absence of semantic labelling in the task means that interpretation of the data is necessarily subjective, and the amount of time required to perform pairwise comparisons on a large number of sounds is potentially prohibitive. Here we present an evidence-based account of semantic categories of sounds commonly described in the soundscape literature, using a robust method based upon perceptual data generated by an online sorting and category-labelling task. This method is relatively quick to perform and elicits rather than prescribes categories and descriptive terms.
DOI: 10.25144/24442
Language: English
Topic: Noise Effects and Management
Subfield: Speech and Hearing
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2906071163