Communication interface for bone-conducted sounds

Technology has been a major advancement factor in human way of living. By integrating technology with our daily activities and processes, automated and interactive smart systems are widely available around us nowadays. One of the domain of which technology has been widely being developed is in medic...

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Main Author: Suryani Simon Turtan.
Other Authors: Song Qing
Format: Final Year Project
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/38859
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-388592023-07-07T17:09:01Z Communication interface for bone-conducted sounds Suryani Simon Turtan. Song Qing School of Electrical and Electronic Engineering A*STAR Institute for Infocomm Research Dr. Tran Huy Dat DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Technology has been a major advancement factor in human way of living. By integrating technology with our daily activities and processes, automated and interactive smart systems are widely available around us nowadays. One of the domain of which technology has been widely being developed is in medical environment. Many disabled people have benefited from the vast developments of technology. For example, speech recognition system which has been applied to aid hearing disabled people to communicate with the world. The project aimed to provide an advancement of sound recognition technology in order to enhance the lives of speech disabled people, including paralyzed patients in hospitals. Classification is one of main processes in sound recognition system, together with feature extraction. Mel Frequency Cepstral Coefficient (MFCC) feature extraction method is implemented due to its capability to simulate human hearing processes, together with Proximal Support Vector Machine (PSVM) as the classifier. The main objective of the project is to improve the original classification system available to be able to process bone-conducted sound produced by the vibration of bone and body surface when words are non-audibly articulated. Studies and experiments on semi-supervised learning method and learning strategy to enhance the classifier’s performance were also being conducted. Bachelor of Engineering 2010-05-20T01:32:53Z 2010-05-20T01:32:53Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/38859 en Nanyang Technological University 68 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::Control and instrumentation::Medical electronics
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
Suryani Simon Turtan.
Communication interface for bone-conducted sounds
description Technology has been a major advancement factor in human way of living. By integrating technology with our daily activities and processes, automated and interactive smart systems are widely available around us nowadays. One of the domain of which technology has been widely being developed is in medical environment. Many disabled people have benefited from the vast developments of technology. For example, speech recognition system which has been applied to aid hearing disabled people to communicate with the world. The project aimed to provide an advancement of sound recognition technology in order to enhance the lives of speech disabled people, including paralyzed patients in hospitals. Classification is one of main processes in sound recognition system, together with feature extraction. Mel Frequency Cepstral Coefficient (MFCC) feature extraction method is implemented due to its capability to simulate human hearing processes, together with Proximal Support Vector Machine (PSVM) as the classifier. The main objective of the project is to improve the original classification system available to be able to process bone-conducted sound produced by the vibration of bone and body surface when words are non-audibly articulated. Studies and experiments on semi-supervised learning method and learning strategy to enhance the classifier’s performance were also being conducted.
author2 Song Qing
author_facet Song Qing
Suryani Simon Turtan.
format Final Year Project
author Suryani Simon Turtan.
author_sort Suryani Simon Turtan.
title Communication interface for bone-conducted sounds
title_short Communication interface for bone-conducted sounds
title_full Communication interface for bone-conducted sounds
title_fullStr Communication interface for bone-conducted sounds
title_full_unstemmed Communication interface for bone-conducted sounds
title_sort communication interface for bone-conducted sounds
publishDate 2010
url http://hdl.handle.net/10356/38859
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