Machine learning / deep learning approach to soundscape evaluations
Masking is the addition of sounds to soundscapes or noise-polluted areas. These additional sounds are known as “maskers”. Soundscape augmentation is a method that involves the addition of “maskers” to a soundscape. It is a noise mitigation method that aims to improve the overall soundscape per...
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2023
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sg-ntu-dr.10356-1674242023-07-07T15:43:36Z Machine learning / deep learning approach to soundscape evaluations Phang, Rachel Rei Xuan Gan Woon Seng School of Electrical and Electronic Engineering EWSGAN@ntu.edu.sg Engineering::Electrical and electronic engineering Masking is the addition of sounds to soundscapes or noise-polluted areas. These additional sounds are known as “maskers”. Soundscape augmentation is a method that involves the addition of “maskers” to a soundscape. It is a noise mitigation method that aims to improve the overall soundscape perception or quality. Many studies have used such techniques to improve the perception of a soundscape. However, the studies conducted have some limitations. The choice of maskers used in those studies are often limited to a single type of masker and are inflexible to real-time soundscapes. The method for selecting maskers also tends to be dependent on experts. This project will be using a machine learning/deep learning approach to select maskers from the given masker database for a soundscape, which can instantaneously and independently predict a suitable masker for that soundscape to create an overall pleasant soundscape. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-28T11:49:50Z 2023-05-28T11:49:50Z 2023 Final Year Project (FYP) Phang, R. R. X. (2023). Machine learning / deep learning approach to soundscape evaluations. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167424 https://hdl.handle.net/10356/167424 en A3103-221 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Phang, Rachel Rei Xuan Machine learning / deep learning approach to soundscape evaluations |
description |
Masking is the addition of sounds to soundscapes or noise-polluted areas. These additional
sounds are known as “maskers”. Soundscape augmentation is a method that involves the
addition of “maskers” to a soundscape. It is a noise mitigation method that aims to improve
the overall soundscape perception or quality.
Many studies have used such techniques to improve the perception of a soundscape.
However, the studies conducted have some limitations. The choice of maskers used in
those studies are often limited to a single type of masker and are inflexible to real-time
soundscapes. The method for selecting maskers also tends to be dependent on experts.
This project will be using a machine learning/deep learning approach to select maskers
from the given masker database for a soundscape, which can instantaneously and
independently predict a suitable masker for that soundscape to create an overall pleasant
soundscape. |
author2 |
Gan Woon Seng |
author_facet |
Gan Woon Seng Phang, Rachel Rei Xuan |
format |
Final Year Project |
author |
Phang, Rachel Rei Xuan |
author_sort |
Phang, Rachel Rei Xuan |
title |
Machine learning / deep learning approach to soundscape evaluations |
title_short |
Machine learning / deep learning approach to soundscape evaluations |
title_full |
Machine learning / deep learning approach to soundscape evaluations |
title_fullStr |
Machine learning / deep learning approach to soundscape evaluations |
title_full_unstemmed |
Machine learning / deep learning approach to soundscape evaluations |
title_sort |
machine learning / deep learning approach to soundscape evaluations |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/167424 |
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1772827537122000896 |