Noise tagging and perceptually-informed unsupervised clustering

Airforce training was deemed both necessary and crucial for the country. However, the persistent issue of aircraft noise had long been a concern for residents living near the air base. This study aimed to explore the realm of sound analysis and data processing concerning the diverse and loud acousti...

Full description

Saved in:
Bibliographic Details
Main Author: Cai, HongLing
Other Authors: Gan Woon Seng
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/172709
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-172709
record_format dspace
spelling sg-ntu-dr.10356-1727092023-12-22T15:44:07Z Noise tagging and perceptually-informed unsupervised clustering Cai, HongLing Gan Woon Seng School of Electrical and Electronic Engineering EWSGAN@ntu.edu.sg Engineering::Electrical and electronic engineering Airforce training was deemed both necessary and crucial for the country. However, the persistent issue of aircraft noise had long been a concern for residents living near the air base. This study aimed to explore the realm of sound analysis and data processing concerning the diverse and loud acoustic disturbances experienced by the residents. The objective was to investigate clustering techniques that could be applied for perceptually-informed unsupervised clustering of sound events, allowing for the automatic analysis of complex audio data. The study involved the development and execution of methods for extracting specific urban sound events from long-term recordings, which addressed the analysis measures used to detect or identify sound events. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-12-19T02:23:37Z 2023-12-19T02:23:37Z 2021 Final Year Project (FYP) Cai, H. (2023). Noise tagging and perceptually-informed unsupervised clustering. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172709 https://hdl.handle.net/10356/172709 en A3107-221 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Cai, HongLing
Noise tagging and perceptually-informed unsupervised clustering
description Airforce training was deemed both necessary and crucial for the country. However, the persistent issue of aircraft noise had long been a concern for residents living near the air base. This study aimed to explore the realm of sound analysis and data processing concerning the diverse and loud acoustic disturbances experienced by the residents. The objective was to investigate clustering techniques that could be applied for perceptually-informed unsupervised clustering of sound events, allowing for the automatic analysis of complex audio data. The study involved the development and execution of methods for extracting specific urban sound events from long-term recordings, which addressed the analysis measures used to detect or identify sound events.
author2 Gan Woon Seng
author_facet Gan Woon Seng
Cai, HongLing
format Final Year Project
author Cai, HongLing
author_sort Cai, HongLing
title Noise tagging and perceptually-informed unsupervised clustering
title_short Noise tagging and perceptually-informed unsupervised clustering
title_full Noise tagging and perceptually-informed unsupervised clustering
title_fullStr Noise tagging and perceptually-informed unsupervised clustering
title_full_unstemmed Noise tagging and perceptually-informed unsupervised clustering
title_sort noise tagging and perceptually-informed unsupervised clustering
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/172709
_version_ 1787136810273472512