SleepSound: Charting the Nighttime Soundscape and Sleep Quality in Hong Kong through Machine Listening and AI-supported Information Design
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| Main Authors: | , , , |
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2025
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| _version_ | 1866902319416737792 |
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| author | Lindborg, PerMagnus Lenzi, Sara Shirley Xin, Li Xiao, Li |
| author_facet | Lindborg, PerMagnus Lenzi, Sara Shirley Xin, Li Xiao, Li |
| contents | <p>Sleep is an essential part of health. One factor that affects sleep quality is soundscape, the acoustic environment as perceived. In the <em>SleepSound</em> project, we aim to collect field data and harness machine listening for an AI-supported assessment of soundscape quality for healthy sleep. Why is this important? Our initial literature review reveals that there is little known about Hong Kong’s domestic acoustic environment and practically no research has been published on people’s perception of their own nighttime soundscape, or how it may affect sleep. A case in point is the Noise Control Ordinance (1989), which regulates noise from e.g. construction sites but leaves much of neighbourhood environments open to interpretation. Without a deeper understanding of soundscape, solving inevitable conflicts might be left to arbitrary judgements. Given this situation, our project aims to develop methods to chart the nighttime soundscape and its impact on sleep. Restorative sleep is important for everyone and crucial for vulnerable individuals e.g. with a medical condition. The present research project builds on our recent study in a nighttime hospital ward, where patients wore sleep trackers to detect disturbances, and soundscape audio was captured. <em>SleepSound</em> will venture further by focusing on the context of domestic bedrooms for normally healthy residents in Hong Kong.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15032456 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | SleepSound: Charting the Nighttime Soundscape and Sleep Quality in Hong Kong through Machine Listening and AI-supported Information Design Lindborg, PerMagnus Lenzi, Sara Shirley Xin, Li Xiao, Li <p>Sleep is an essential part of health. One factor that affects sleep quality is soundscape, the acoustic environment as perceived. In the <em>SleepSound</em> project, we aim to collect field data and harness machine listening for an AI-supported assessment of soundscape quality for healthy sleep. Why is this important? Our initial literature review reveals that there is little known about Hong Kong’s domestic acoustic environment and practically no research has been published on people’s perception of their own nighttime soundscape, or how it may affect sleep. A case in point is the Noise Control Ordinance (1989), which regulates noise from e.g. construction sites but leaves much of neighbourhood environments open to interpretation. Without a deeper understanding of soundscape, solving inevitable conflicts might be left to arbitrary judgements. Given this situation, our project aims to develop methods to chart the nighttime soundscape and its impact on sleep. Restorative sleep is important for everyone and crucial for vulnerable individuals e.g. with a medical condition. The present research project builds on our recent study in a nighttime hospital ward, where patients wore sleep trackers to detect disturbances, and soundscape audio was captured. <em>SleepSound</em> will venture further by focusing on the context of domestic bedrooms for normally healthy residents in Hong Kong.</p> |
| title | SleepSound: Charting the Nighttime Soundscape and Sleep Quality in Hong Kong through Machine Listening and AI-supported Information Design |
| url | https://doi.org/10.5281/zenodo.15032456 |