TY - JOUR SN - 0360-1323 N1 - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions. ID - discovery10198304 AV - restricted JF - Building and Environment N2 - 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 (? = 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 ?A,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. VL - 266 PB - Elsevier BV Y1 - 2024/12/01/ A1 - Lam, Bhan A1 - Ong, Zhen-Ting A1 - Ooi, Kenneth A1 - Ong, Wen-Hui A1 - Wong, Trevor A1 - Watcharasupat, Karn N A1 - Boey, Vanessa A1 - Lee, Irene A1 - Hong, Joo Young A1 - Kang, Jian A1 - Lee, Kar Fye Alvin A1 - Christopoulos, Georgios A1 - Gan, Woon-Seng UR - https://doi.org/10.1016/j.buildenv.2024.112106 TI - Automating urban soundscape enhancements with AI: In-situ assessment of quality and restorativeness in traffic-exposed residential areas KW - Urban soundscape KW - natural sounds KW - auditory masking KW - probabilistic approach KW - soundscape augmentation KW - artificial intelligence ER -