Investigating real indoor soundscapes and their predictability for known and unknown subjects [Vortrag]

  • Understanding people's perception of everyday sound involves a complex interplay of various acoustic and non-acoustic factors. Our objective is to uncover important predictors for predicting real indoor soundscapes. To this end, we re-analyzed soundscape data recorded and evaluated by individuals in their homes, aiming for the utmost ecological validity. Given the intricate nature of sound perception and potential non-linear effects of acoustic and psychoacoustic predictors, we utilized machine-learning methods combined with hierarchical linear modeling to analyze 6375 soundscapes from 96 participants including acoustical, psychoacoustical, as well as situational und person-related predictors. Based on this analysis, we measured both the variability within and between subjects and obtained model fits for the prediction of both soundscape pleasantness and eventfulness. In order to discuss cases where predictions for known individuals or places are of interest, we employed (nested)Understanding people's perception of everyday sound involves a complex interplay of various acoustic and non-acoustic factors. Our objective is to uncover important predictors for predicting real indoor soundscapes. To this end, we re-analyzed soundscape data recorded and evaluated by individuals in their homes, aiming for the utmost ecological validity. Given the intricate nature of sound perception and potential non-linear effects of acoustic and psychoacoustic predictors, we utilized machine-learning methods combined with hierarchical linear modeling to analyze 6375 soundscapes from 96 participants including acoustical, psychoacoustical, as well as situational und person-related predictors. Based on this analysis, we measured both the variability within and between subjects and obtained model fits for the prediction of both soundscape pleasantness and eventfulness. In order to discuss cases where predictions for known individuals or places are of interest, we employed (nested) cross-validation using different data-splitting methods. By doing so, our study sheds light on the generalizability of empirical findings when predicting soundscape evaluations for unknown or known subjects and thus supports a deeper understanding of everyday sound perception.show moreshow less

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Metadaten
Author:Siegbert Versümer, Jochen Steffens
Institutes:Institute of Sound and Vibration Engineering (ISAVE)
Fachbereich/Einrichtung:Hochschule Düsseldorf / Fachbereich - Medien
Document Type:Conference Proceeding
Year of Completion:2024
Language of Publication:English
Publisher:Deutsche Gesellschaft für Akustik e.V.
Place of publication:Berlin
Parent Title (English):Fortschritte der Akustik - DAGA 2024, 18. - 21. März 2024, Hannover
Tag:Vortrag
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Licence (German):keine Lizenz - nur Metadaten
Release Date:2025/05/22
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