Lam, Bhan;
Ong, Zhen-Ting;
Ooi, Kenneth;
Ong, Wen-Hui;
Wong, Trevor;
Watcharasupat, Karn N;
Boey, Vanessa;
... Gan, Woon-Seng; + view all
(2024)
Automating urban soundscape enhancements with AI: In-situ assessment of quality and restorativeness in traffic-exposed residential areas.
Building and Environment
, 266
, Article 112106. 10.1016/j.buildenv.2024.112106.
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BAE_2024.112106_accepted_preprint.pdf - Accepted Version Access restricted to UCL open access staff until 29 September 2025. Download (6MB) |
Abstract
Formalized in ISO 12913, the “soundscape” approach is a paradigmatic shift towards perceptionbased urban sound management, aiming to alleviate the substantial socioeconomic costs of noise pollution to advance the United Nations Sustainable Development Goals. Focusing on traffic-exposed outdoor residential sites, we implemented an automatic masker selection system (AMSS) utilizing natural sounds to mask (or augment) traffic soundscapes. We employed a pre-trained AI model to automatically select the optimal masker and adjust its playback level, adapting to changes over time in the ambient environment to maximize “Pleasantness”, a perceptual dimension of soundscape quality in ISO 12913. Our validation study involving (푁 = 68) residents revealed a significant 14.6 % enhancement in “Pleasantness” after intervention, correlating with increased restorativeness and positive affect. Perceptual enhancements at the traffic-exposed site matched those at a quieter control site with 6 dB(A) lower 퐿A,eq and road traffic noise dominance, affirming the efficacy of AMSS as a soundscape intervention, while streamlining the labour-intensive assessment of “Pleasantness” with probabilistic AI prediction.
| Type: | Article |
|---|---|
| Title: | Automating urban soundscape enhancements with AI: In-situ assessment of quality and restorativeness in traffic-exposed residential areas |
| DOI: | 10.1016/j.buildenv.2024.112106 |
| Publisher version: | https://doi.org/10.1016/j.buildenv.2024.112106 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Urban soundscape, natural sounds, auditory masking, probabilistic approach, soundscape augmentation, artificial intelligence |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10198304 |
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