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Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification

Most insects and animal produce sounds as a way of communication within their species or as noises resulting from feeding or travelling. Automated recognition of bio-acoustic signals is becoming vital in the aspect of biological research or environmental monitoring. With the improvement of technol...

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Main Author: Wan, Zhi Xuan
Format: Monograph
Language:English
Published: Universiti Sains Malaysia 2018
Subjects:
T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
Online Access:http://eprints.usm.my/53308/1/Bio%20Acoustic%20Signal%20Identification%20Based%20On%20Sparse%20Representation%20Classifier%20Frog%20Species%20Voice%20Identification_Wan%20Zhi%20Xuan_E3_2018.pdf
http://eprints.usm.my/53308/
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spelling my.usm.eprints.53308 http://eprints.usm.my/53308/ Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification Wan, Zhi Xuan T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Most insects and animal produce sounds as a way of communication within their species or as noises resulting from feeding or travelling. Automated recognition of bio-acoustic signals is becoming vital in the aspect of biological research or environmental monitoring. With the improvement of technology, scientists today are able to classify types and species of animals by their vocalizations without even need to see the animal or insects with naked eye. Hence, species identification based on their calls or vocalization is an important topic to enhance in the aspect of ecological research. This project aims to develop a frog species voice identification system, recognizing different frog species through analyzing their calls. In the data acquisition stage, databases from Intelligent Biometric Research Group (IBG), School of Electrical and Electronics Engineering, Universiti Sains Malaysia in collaboration with School of Pharmacy, Universiti Sains Malaysia have been used to evaluate the performance of the system. Raw frog call files are processed using Mel-Frequency Cepstral Coefficient (MFCC) technique to extract features that will be needed in testing and training the system. In this project, the classifier used is Sparse Representation Classifier (SRC) and Kernel Sparse Representation Classifier (KSRC). Performance between SRC and KSRC is compared and discussed in this project. Besides, a graphic user interface (GUI) is also developed to facilitate the user while interacting with the system. Two experiments were done in this project, both using SRC and KSRC. In short, KSRC (96.6667%) has a higher performance in accuracy compared to SRC (95.6667%). However, KSRC takes a longer computation time compared to SRC. A GUI was developed implementing KSRC with feature dimension of 64-by-64 as an outcome of this project. Universiti Sains Malaysia 2018-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53308/1/Bio%20Acoustic%20Signal%20Identification%20Based%20On%20Sparse%20Representation%20Classifier%20Frog%20Species%20Voice%20Identification_Wan%20Zhi%20Xuan_E3_2018.pdf Wan, Zhi Xuan (2018) Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik dan Elektronik. (Submitted)
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
spellingShingle T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
Wan, Zhi Xuan
Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification
description Most insects and animal produce sounds as a way of communication within their species or as noises resulting from feeding or travelling. Automated recognition of bio-acoustic signals is becoming vital in the aspect of biological research or environmental monitoring. With the improvement of technology, scientists today are able to classify types and species of animals by their vocalizations without even need to see the animal or insects with naked eye. Hence, species identification based on their calls or vocalization is an important topic to enhance in the aspect of ecological research. This project aims to develop a frog species voice identification system, recognizing different frog species through analyzing their calls. In the data acquisition stage, databases from Intelligent Biometric Research Group (IBG), School of Electrical and Electronics Engineering, Universiti Sains Malaysia in collaboration with School of Pharmacy, Universiti Sains Malaysia have been used to evaluate the performance of the system. Raw frog call files are processed using Mel-Frequency Cepstral Coefficient (MFCC) technique to extract features that will be needed in testing and training the system. In this project, the classifier used is Sparse Representation Classifier (SRC) and Kernel Sparse Representation Classifier (KSRC). Performance between SRC and KSRC is compared and discussed in this project. Besides, a graphic user interface (GUI) is also developed to facilitate the user while interacting with the system. Two experiments were done in this project, both using SRC and KSRC. In short, KSRC (96.6667%) has a higher performance in accuracy compared to SRC (95.6667%). However, KSRC takes a longer computation time compared to SRC. A GUI was developed implementing KSRC with feature dimension of 64-by-64 as an outcome of this project.
format Monograph
author Wan, Zhi Xuan
author_facet Wan, Zhi Xuan
author_sort Wan, Zhi Xuan
title Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification
title_short Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification
title_full Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification
title_fullStr Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification
title_full_unstemmed Bio Acoustic Signal Identification Based On Sparse Representation Classifier Frog Species Voice Identification
title_sort bio acoustic signal identification based on sparse representation classifier frog species voice identification
publisher Universiti Sains Malaysia
publishDate 2018
url http://eprints.usm.my/53308/1/Bio%20Acoustic%20Signal%20Identification%20Based%20On%20Sparse%20Representation%20Classifier%20Frog%20Species%20Voice%20Identification_Wan%20Zhi%20Xuan_E3_2018.pdf
http://eprints.usm.my/53308/
_version_ 1738511186841829376
score 13.211869

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