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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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 |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Tan, Ivan Yun Feng Gender classification using audio features in mobile devices |
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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. |
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Chng Eng Siong |
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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 |
_version_ |
1759856831734218752 |