Gender classification using audio features in mobile devices

This FYP project is to develop a voice based gender classification mobile application on the android platform. The purpose of the project was to understand the process and techniques involved in a voice verification system. Then from the knowledge obtained, apply it into developing a mobile applicat...

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Main Author: Tan, Ivan Yun Feng
Other Authors: Chng Eng Siong
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/59064
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-590642023-03-03T20:35:01Z Gender classification using audio features in mobile devices Tan, Ivan Yun Feng Chng Eng Siong School of Computer Engineering Emerging Research Lab DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition This FYP project is to develop a voice based gender classification mobile application on the android platform. The purpose of the project was to understand the process and techniques involved in a voice verification system. Then from the knowledge obtained, apply it into developing a mobile application on one of the most commonly found mobile platform in the current market. The application is targeted to work on phone running android version between 2.2 to 4.3. A Samsung galaxy S2 phone running version 4.1.2 is use through the development and testing period. In this application, it allows the user to generate the voice characteristic of him/her and use it to run the gender classification test swiftly and come up with the result of the possible gender. From the experiment conducted, it is concluded that increase in sample size or mixture alone will not get the optimum accuracy. Instead pairing of adequate mixture based on the sample data size is needed. Also the application had 75.88% classification accuracy. Recommendations are made on the improving the visual aspect of the interface and increasing the number of voice related functionality such as age group classification and even speaker identification. Likewise more tests from different sources can be conducted. Bachelor of Engineering (Computer Engineering) 2014-04-22T03:22:28Z 2014-04-22T03:22:28Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59064 en Nanyang Technological University 48 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::Computer science and engineering::Computing methodologies::Pattern recognition
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Tan, Ivan Yun Feng
Gender classification using audio features in mobile devices
description This FYP project is to develop a voice based gender classification mobile application on the android platform. The purpose of the project was to understand the process and techniques involved in a voice verification system. Then from the knowledge obtained, apply it into developing a mobile application on one of the most commonly found mobile platform in the current market. The application is targeted to work on phone running android version between 2.2 to 4.3. A Samsung galaxy S2 phone running version 4.1.2 is use through the development and testing period. In this application, it allows the user to generate the voice characteristic of him/her and use it to run the gender classification test swiftly and come up with the result of the possible gender. From the experiment conducted, it is concluded that increase in sample size or mixture alone will not get the optimum accuracy. Instead pairing of adequate mixture based on the sample data size is needed. Also the application had 75.88% classification accuracy. Recommendations are made on the improving the visual aspect of the interface and increasing the number of voice related functionality such as age group classification and even speaker identification. Likewise more tests from different sources can be conducted.
author2 Chng Eng Siong
author_facet Chng Eng Siong
Tan, Ivan Yun Feng
format Final Year Project
author Tan, Ivan Yun Feng
author_sort Tan, Ivan Yun Feng
title Gender classification using audio features in mobile devices
title_short Gender classification using audio features in mobile devices
title_full Gender classification using audio features in mobile devices
title_fullStr Gender classification using audio features in mobile devices
title_full_unstemmed Gender classification using audio features in mobile devices
title_sort gender classification using audio features in mobile devices
publishDate 2014
url http://hdl.handle.net/10356/59064
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