Yang, Qingyang (2024) Effects of sound masking noise on workers’ perception and performance. Masters thesis, Concordia University.
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Abstract
There is always a lack of separation between individual work areas in open offices, so sound insulation is poor. A cheap and effective solution to this problem may be to use sound masking technology. This study aims to explore the impact of sound masking noise on employee perception and psychology in scenarios involving two types of signal speech noise involving sound masking technology. Specifically, this study implemented background noise, speech, visual stimuli, and interactive components required in a real-time virtual reality framework. Ten participants participated in a multi-task cognitive experiment. The key metrics for evaluation include task completion rate, accuracy, NASA Task Load Index, and individual noise sensitivity scores.
The average accuracy is lower in the 50 dBA with speech condition compared to the 38 dBA with speech condition. Similarly, participants complete fewer math questions on average in the 50 dBA with speech condition compared to the 38 dBA with speech condition. The combination of higher noise levels and speech (bad signal-to-noise ratio for speech) significantly hampers task efficiency. It shows that the ten participants have different levels of sensitivity to noise or speech. People with higher noise sensitivity will experience the highest task load in noisy environments with speech. In environments with irregular noise patterns, sound masking systems may inadvertently amplify rather than mask irregular noise. This study not only observed individual differences in noise sensitivity and cognitive effects, but also highlighted the importance of individual responses to noise in managing noise exposure in the open plan offices.
Keywords: sound masking
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Yang, Qingyang |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Building Engineering |
Date: | July 2024 |
Thesis Supervisor(s): | Lee, Joonhee |
ID Code: | 994661 |
Deposited By: | Qingyang Wang |
Deposited On: | 25 Oct 2024 15:04 |
Last Modified: | 25 Oct 2024 15:04 |
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