Author (s)
Zhen-Ting Ong 1, Joo-Young Hong 1, Bhan Lam 1, Kenneth Ooi 1, Woon-Seng Gan 1, Samuel Yeong 2, Irene Lee 2, Sze-Tiong Tan 2
Affiliation
1 School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore
2 Building & Research Institute, Housing & Development Board, Singapore
Publication date
2019
Abstract
Augmenting pleasant natural sounds in the noisy urban environment is a key strategy in soundscape design. There have been numerous studies on the positive effects of natural sounds on soundscape quality. However, little attention has been directed to predictive models that suggest appropriate levels of natural sounds at specific ambient noise levels. These models provide a blueprint for practical soundscape design. This study, thus, aims to develop prediction models of desirable natural sound levels (birdsong and water sound) to enhance the soundscape quality through laboratory experiments based on virtual reality. The laboratory test consists of two steps (I and II). In step I, participants were instructed to evaluate traffic sound scenes, ranging from 60 to 70 dB, in terms of perceived loudness of noise (PLN) and overall soundscape quality (OSQ). In step II, the participants were instructed to adjust the audio levels of bird or water sounds augmented to each traffic scene to the most desirable levels while considering the preceding PLN of traffic and OSQ. Based on the results, the soundscape predictive models were developed using acoustic indicators to predict the desirable natural sound levels corresponding to traffic noise levels.
Full paper
https://publications.rwth-aachen.de/record/770006/files/770006.pdf
Keywords
soundscape, virtual reality, ecological validity, parametric decoding, ambisonics