Stream-sound augmentation of traffic noise in virtual reality: experimental dataset

Description

This is the analysis-ready dataset underlying a within-participant virtual-reality experiment on stream-sound augmentation of traffic noise. Fifty young adults each experienced one historic urban square (a virtual-reality reconstruction of Zhongshan Square, Shenyang) under four traffic-sound levels (54, 57, 60 and 63 dB(A)), each presented without and with the same water-stream recording at a -3 dB signal-to-noise ratio, giving a 4x2 within-participant design in Latin-square order of about 32 minutes per participant. For every participant-and-condition combination the table records the traffic stimulus's psychoacoustic properties (loudness, sharpness, roughness and fluctuation strength), subjective soundscape ratings (ISO 12913 pleasantness and eight bipolar attributes), and noise-sensitivity, WHO-5 wellbeing and virtual-reality-comfort covariates, together with supporting electroencephalography (EEG) and electrodermal-activity (EDA) indices. All fifty participants provided subjective ratings; 39 yielded usable EEG and 43 usable EDA. The data address three questions examined in the accompanying manuscript: the average affective benefit of stream-sound augmentation across the traffic-exposure gradient, which experiential dimension (valence versus activation) changes, and whether the reach and predictability of individual benefits favour broad or targeted provision. Records carry anonymous participant identifiers only (A-1 to A-50), with participant, traffic level and stream state forming the primary key. The dataset is released under CC BY 4.0 and should be cited together with the associated article.

Institutions

• Shenyang Jianzhu University

  Liaoning, Shenyang

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