An internet of things approach to auditory masker fusion and investigation into spatial locomotion for soundscape augmentation utilizing 5G communication

• Main Author: Wong, Trevor Martens Zhi Ming
• Other Authors: Gan Woon Seng
• Format: Thesis-Master by Research
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; Soundscape; IoT
• Online Access: https://hdl.handle.net/10356/178329
• Institution: Nanyang Technological University

The soundscape approach is a holistic approach to improving the perceptual attributes of an acoustic environment, such as pleasantness. An approach known as soundscape augmentation helps to improve pleasantness by introducing new sounds, or maskers, into the soundscape. A machine learning based system exists to predict the best maskers for soundscape augmentation but is challenging to implement in a real-world environment. In this work, an Internet of Things (IoT) system is designed to allow for a low-cost implementation of this machine learning system, allowing intelligent soundscape augmentation with minimal human intervention. A prototype of this system was set up in a public space and a pilot study conducted to verify its effectiveness. Additionally, locomotion of maskers and the use of multiple maskers are under-explored areas of soundscape augmentation. While the directionality of maskers has been shown to affect soundscape quality, research on maskers spatialized to “move” about the listener is lacking. This work explored whether adding locomotion to the predicted maskers and whether using more than one masker at a time would impact pleasantness for listeners through a subjective experiment with 29 participants. The results of the experiment showed no significant impact on pleasantness due to locomotion or multiple maskers. As a result, it was determined that the design of the IoT soundscape augmentation system could be simplified in future iterations, eliminating the need for a first order ambisonic playback system. This would reduce cost and complexity in future designs, improving the efficiency of the system.