Cover Image

Signal-based feature extraction for makhraj emission point classification

Due to the similar sound of one letter to the others, mistakes might happen when pronouncing a hijaiyah letter. The reciter will not read the Quran correctly if they do not understand the relationship between the hijaiyah letter sound and its point of articulation. This study addresses the issue to...

Full description

Saved in:
Bibliographic Details
Main Authors: Nurul Wahidah, Arshad, Mohd Zamri, Ibrahim, Rohana, Abdul Karim, Yasmin, Abdul Wahab, Nor Farizan, Zakaria, Tuan Sidek, Tuan Muda
Format: Conference or Workshop Item
Language:English
English
Published: Institution of Engineering and Technology 2022
Subjects:
H Social Sciences (General)
Q Science (General)
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/41947/1/Signal-based%20feature%20extraction%20for%20makhraj%20emission.pdf
http://umpir.ump.edu.my/id/eprint/41947/2/Signal-based%20feature%20extraction%20for%20makhraj%20emission%20point%20classification_ABS.pdf
http://umpir.ump.edu.my/id/eprint/41947/
https://doi.org/10.1049/icp.2022.2562
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ump.umpir.41947
record_format eprints
spelling my.ump.umpir.419472024-08-30T00:21:33Z http://umpir.ump.edu.my/id/eprint/41947/ Signal-based feature extraction for makhraj emission point classification Nurul Wahidah, Arshad Mohd Zamri, Ibrahim Rohana, Abdul Karim Yasmin, Abdul Wahab Nor Farizan, Zakaria Tuan Sidek, Tuan Muda H Social Sciences (General) Q Science (General) T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Due to the similar sound of one letter to the others, mistakes might happen when pronouncing a hijaiyah letter. The reciter will not read the Quran correctly if they do not understand the relationship between the hijaiyah letter sound and its point of articulation. This study addresses the issue to recognize the nine points of articulation (throat, uvular, molar, palatal, alveolar, dental, alveolar dental, lip, and interdental) from makhraj recitation using speech processing technique. As much as 181 non-distributive audio samples recorded in control environment. The input speech is a sukun combination of the Hijaiyah letter from an expert reciter. The research uses 5 type of signal-based feature extraction methods (MFCC, chroma, Mel spectrogram, spectral contract, and Tonnetz) and three type of classification methods (ANN, kNN, and SVM). The result shows the proposed method obtained a fair accuracy with the highest accuracy is 56% using ANN. Institution of Engineering and Technology 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/41947/1/Signal-based%20feature%20extraction%20for%20makhraj%20emission.pdf pdf en http://umpir.ump.edu.my/id/eprint/41947/2/Signal-based%20feature%20extraction%20for%20makhraj%20emission%20point%20classification_ABS.pdf Nurul Wahidah, Arshad and Mohd Zamri, Ibrahim and Rohana, Abdul Karim and Yasmin, Abdul Wahab and Nor Farizan, Zakaria and Tuan Sidek, Tuan Muda (2022) Signal-based feature extraction for makhraj emission point classification. In: IET Conference Proceedings. 2022 Engineering Technology International Conference, ETIC 2022 , 7 - 8 September 2022 , Kuantan, Virtual. pp. 19-25., 2022 (22). ISSN 2732-4494 ISBN 978-183953782-0 (Published) https://doi.org/10.1049/icp.2022.2562
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic H Social Sciences (General)
Q Science (General)
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle H Social Sciences (General)
Q Science (General)
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Nurul Wahidah, Arshad
Mohd Zamri, Ibrahim
Rohana, Abdul Karim
Yasmin, Abdul Wahab
Nor Farizan, Zakaria
Tuan Sidek, Tuan Muda
Signal-based feature extraction for makhraj emission point classification
description Due to the similar sound of one letter to the others, mistakes might happen when pronouncing a hijaiyah letter. The reciter will not read the Quran correctly if they do not understand the relationship between the hijaiyah letter sound and its point of articulation. This study addresses the issue to recognize the nine points of articulation (throat, uvular, molar, palatal, alveolar, dental, alveolar dental, lip, and interdental) from makhraj recitation using speech processing technique. As much as 181 non-distributive audio samples recorded in control environment. The input speech is a sukun combination of the Hijaiyah letter from an expert reciter. The research uses 5 type of signal-based feature extraction methods (MFCC, chroma, Mel spectrogram, spectral contract, and Tonnetz) and three type of classification methods (ANN, kNN, and SVM). The result shows the proposed method obtained a fair accuracy with the highest accuracy is 56% using ANN.
format Conference or Workshop Item
author Nurul Wahidah, Arshad
Mohd Zamri, Ibrahim
Rohana, Abdul Karim
Yasmin, Abdul Wahab
Nor Farizan, Zakaria
Tuan Sidek, Tuan Muda
author_facet Nurul Wahidah, Arshad
Mohd Zamri, Ibrahim
Rohana, Abdul Karim
Yasmin, Abdul Wahab
Nor Farizan, Zakaria
Tuan Sidek, Tuan Muda
author_sort Nurul Wahidah, Arshad
title Signal-based feature extraction for makhraj emission point classification
title_short Signal-based feature extraction for makhraj emission point classification
title_full Signal-based feature extraction for makhraj emission point classification
title_fullStr Signal-based feature extraction for makhraj emission point classification
title_full_unstemmed Signal-based feature extraction for makhraj emission point classification
title_sort signal-based feature extraction for makhraj emission point classification
publisher Institution of Engineering and Technology
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/41947/1/Signal-based%20feature%20extraction%20for%20makhraj%20emission.pdf
http://umpir.ump.edu.my/id/eprint/41947/2/Signal-based%20feature%20extraction%20for%20makhraj%20emission%20point%20classification_ABS.pdf
http://umpir.ump.edu.my/id/eprint/41947/
https://doi.org/10.1049/icp.2022.2562
_version_ 1822924598222520320
score 13.232389

Similar Items