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Web-based Kadazandusun speech recognition system

This project investigates a model for the classification and develops the web-based system of speech recognition for the Kadazandusun language. It is specifically designed for Universiti Malaysia Sabah (UMS) students and lecturers that are studying or teaching the Kadazandusun language. Nowadays, on...

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Bibliographic Details
Main Author: Arrvierri Vespha
Format: Academic Exercise
Language:English
English
Published: 2022
Subjects:
PL5051-5497 Malayan (Indonesian) languages
QA76.75-76.765 Computer software
Online Access:https://eprints.ums.edu.my/id/eprint/33292/1/WEB-BASED%20KADAZANDUSUN%20SPEECH%20RECOGNITION%20SYSTEM.24pages.pdf
https://eprints.ums.edu.my/id/eprint/33292/2/WEB-BASED%20KADAZANDUSUN%20SPEECH%20RECOGNITION%20SYSTEM.pdf
https://eprints.ums.edu.my/id/eprint/33292/
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spelling my.ums.eprints.332922022-07-18T11:19:08Z https://eprints.ums.edu.my/id/eprint/33292/ Web-based Kadazandusun speech recognition system Arrvierri Vespha PL5051-5497 Malayan (Indonesian) languages QA76.75-76.765 Computer software This project investigates a model for the classification and develops the web-based system of speech recognition for the Kadazandusun language. It is specifically designed for Universiti Malaysia Sabah (UMS) students and lecturers that are studying or teaching the Kadazandusun language. Nowadays, only the elderly of the Kadazandusun ethnic are fluent in their language and the majority of the ethnic’s youth cannot speak it fluently yet still understand their language, while some cannot understand the language spoken. This caused the existential crisis of the Kadazandusun language to arise. Furthermore, there are not many speech recognition systems that were developed for the language itself. There is only a little information of research regarding Kadazandusun speech recognition. The main purposes of this project are to investigate, recognize, and evaluate the Kadazandusun language speech recognition based on Mel-frequency Cepstral Coefficient (MFCC), Feed Forward Neural Network, and Principle Component Analysis. A website application is developed which integrates the model for speech recognition system. Based on the investigation (training and testing), the MFCC and Neural Network produce 89.22, 86.82, 87.54, 85.92, and 85.61 mean for classification accuracies using 11, 12, 13, 14, and 15 of MFCC coefficients respectively. Coefficient 11 was chosen as MFCC coefficient therefore it can be used as basic speech recognition for the Kadazandusun. Future works include collecting more data to enhance the usability of admin page, improving the pre-processing method, and hyperparameter tuning, as well as adding new feature to this system. 2022 Academic Exercise NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/33292/1/WEB-BASED%20KADAZANDUSUN%20SPEECH%20RECOGNITION%20SYSTEM.24pages.pdf text en https://eprints.ums.edu.my/id/eprint/33292/2/WEB-BASED%20KADAZANDUSUN%20SPEECH%20RECOGNITION%20SYSTEM.pdf Arrvierri Vespha (2022) Web-based Kadazandusun speech recognition system. Universiti Malaysia Sabah. (Unpublished)
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic PL5051-5497 Malayan (Indonesian) languages
QA76.75-76.765 Computer software
spellingShingle PL5051-5497 Malayan (Indonesian) languages
QA76.75-76.765 Computer software
Arrvierri Vespha
Web-based Kadazandusun speech recognition system
description This project investigates a model for the classification and develops the web-based system of speech recognition for the Kadazandusun language. It is specifically designed for Universiti Malaysia Sabah (UMS) students and lecturers that are studying or teaching the Kadazandusun language. Nowadays, only the elderly of the Kadazandusun ethnic are fluent in their language and the majority of the ethnic’s youth cannot speak it fluently yet still understand their language, while some cannot understand the language spoken. This caused the existential crisis of the Kadazandusun language to arise. Furthermore, there are not many speech recognition systems that were developed for the language itself. There is only a little information of research regarding Kadazandusun speech recognition. The main purposes of this project are to investigate, recognize, and evaluate the Kadazandusun language speech recognition based on Mel-frequency Cepstral Coefficient (MFCC), Feed Forward Neural Network, and Principle Component Analysis. A website application is developed which integrates the model for speech recognition system. Based on the investigation (training and testing), the MFCC and Neural Network produce 89.22, 86.82, 87.54, 85.92, and 85.61 mean for classification accuracies using 11, 12, 13, 14, and 15 of MFCC coefficients respectively. Coefficient 11 was chosen as MFCC coefficient therefore it can be used as basic speech recognition for the Kadazandusun. Future works include collecting more data to enhance the usability of admin page, improving the pre-processing method, and hyperparameter tuning, as well as adding new feature to this system.
format Academic Exercise
author Arrvierri Vespha
author_facet Arrvierri Vespha
author_sort Arrvierri Vespha
title Web-based Kadazandusun speech recognition system
title_short Web-based Kadazandusun speech recognition system
title_full Web-based Kadazandusun speech recognition system
title_fullStr Web-based Kadazandusun speech recognition system
title_full_unstemmed Web-based Kadazandusun speech recognition system
title_sort web-based kadazandusun speech recognition system
publishDate 2022
url https://eprints.ums.edu.my/id/eprint/33292/1/WEB-BASED%20KADAZANDUSUN%20SPEECH%20RECOGNITION%20SYSTEM.24pages.pdf
https://eprints.ums.edu.my/id/eprint/33292/2/WEB-BASED%20KADAZANDUSUN%20SPEECH%20RECOGNITION%20SYSTEM.pdf
https://eprints.ums.edu.my/id/eprint/33292/
_version_ 1760231144316469248
score 13.211869

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