Web audio tagging system

Computational Auditory Scene Analysis (CASA) is the study of auditory scene analysis (ASA) by computational means [1]. The motivation is to allow a machine to have the same capabilities of a human that can separate the mixtures of sounds. In other words, according to Cherry, 1957: “One of our import...

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Main Author: Teo, Sebastian Soon Chuan
Other Authors: Gan Woon Seng
Format: Final Year Project
Language:English
Published: 2018
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Online Access:http://hdl.handle.net/10356/75858
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-758582023-07-07T16:59:23Z Web audio tagging system Teo, Sebastian Soon Chuan Gan Woon Seng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Computational Auditory Scene Analysis (CASA) is the study of auditory scene analysis (ASA) by computational means [1]. The motivation is to allow a machine to have the same capabilities of a human that can separate the mixtures of sounds. In other words, according to Cherry, 1957: “One of our important faculties are our abilities to listen to, and follow, one speaker in the presence of others. We may call it ‘the cocktail party problem’” [1]. The aim of our creation is given the audio, we can identify or classify dominant noise by installing sensors with an analytic computer program. The benefits from implementing this system are, with the increasing number of noise complaints in Singapore over the recent years, government agencies begin to devote more resources to investigate them. [2] However, such complaints are not easy to resolve as the aggravating sounds may stop before the authorities arrive at the site. [2] Hence, this new creation can help the agencies with their work by not only detecting the noises but also identifying them. [2] Furthermore, according to Prof Gan, director of the EEE’s Centre for Infocomm Technology (INFINITUS): “since the sensor can classify the noises, it can also alert only the relevant government agencies thus freeing up precious resources and speeding up the process of resolving the complaint.” Bachelor of Engineering 2018-06-20T09:05:03Z 2018-06-20T09:05:03Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75858 en Nanyang Technological University 125 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Teo, Sebastian Soon Chuan
Web audio tagging system
description Computational Auditory Scene Analysis (CASA) is the study of auditory scene analysis (ASA) by computational means [1]. The motivation is to allow a machine to have the same capabilities of a human that can separate the mixtures of sounds. In other words, according to Cherry, 1957: “One of our important faculties are our abilities to listen to, and follow, one speaker in the presence of others. We may call it ‘the cocktail party problem’” [1]. The aim of our creation is given the audio, we can identify or classify dominant noise by installing sensors with an analytic computer program. The benefits from implementing this system are, with the increasing number of noise complaints in Singapore over the recent years, government agencies begin to devote more resources to investigate them. [2] However, such complaints are not easy to resolve as the aggravating sounds may stop before the authorities arrive at the site. [2] Hence, this new creation can help the agencies with their work by not only detecting the noises but also identifying them. [2] Furthermore, according to Prof Gan, director of the EEE’s Centre for Infocomm Technology (INFINITUS): “since the sensor can classify the noises, it can also alert only the relevant government agencies thus freeing up precious resources and speeding up the process of resolving the complaint.”
author2 Gan Woon Seng
author_facet Gan Woon Seng
Teo, Sebastian Soon Chuan
format Final Year Project
author Teo, Sebastian Soon Chuan
author_sort Teo, Sebastian Soon Chuan
title Web audio tagging system
title_short Web audio tagging system
title_full Web audio tagging system
title_fullStr Web audio tagging system
title_full_unstemmed Web audio tagging system
title_sort web audio tagging system
publishDate 2018
url http://hdl.handle.net/10356/75858
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