Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb

Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel cause difficulties for the non-native Arabic speakers, particularly the Malay speakers, to pronounce these letters correctly. Hence, in this thesis, noise reduction and consonants recognition are conducte...

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Main Author: Almisreb, Ali Abd
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2016
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Online Access:http://ir.uitm.edu.my/id/eprint/19629/1/ABS_ALI%20ABD%20ALMISREB%20TDRA%20VOL%209%20IGS%2016.pdf
http://ir.uitm.edu.my/id/eprint/19629/
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Institution: Universiti Teknologi Mara
Language: English
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spelling my.uitm.ir.196292018-06-07T03:18:40Z http://ir.uitm.edu.my/id/eprint/19629/ Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb Almisreb, Ali Abd Malaysia Language. Linguistic theory. Comparative grammar Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel cause difficulties for the non-native Arabic speakers, particularly the Malay speakers, to pronounce these letters correctly. Hence, in this thesis, noise reduction and consonants recognition are conducted among the Malay speakers. The Malay race has been chosen due to the high usage of the Arabic language for reciting Al-Quran. Generally, the study is divided into two parts, namely, the study of noise reduction and consonant recognition. First, two noise removal methods were developed. The first method is based on combining Negative function with Gamma correction function. The second noise reduction method is addressed by utilising 2D Gabor filter. Furthermore, the consonant study was conducted based on Automatic Speech Recognition (ASR) system concept. The ASR composes of feature extraction stage followed by speech recognition. On the other hand, the feature extraction was implemented by investigating three different methods, namely, Mel-Frequency Cepstrum Coefficients (MFCC), Linear Prediction Coefficients (LPC) and Perceptual Linear Prediction (PLP)… Institute of Graduate Studies, UiTM 2016 Book Section PeerReviewed text en http://ir.uitm.edu.my/id/eprint/19629/1/ABS_ALI%20ABD%20ALMISREB%20TDRA%20VOL%209%20IGS%2016.pdf Almisreb, Ali Abd (2016) Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb. In: The Doctoral Research Abstracts. IGS Biannual Publication, 9 (9). Institute of Graduate Studies, UiTM, Shah Alam.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Malaysia
Language. Linguistic theory. Comparative grammar
spellingShingle Malaysia
Language. Linguistic theory. Comparative grammar
Almisreb, Ali Abd
Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb
description Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel cause difficulties for the non-native Arabic speakers, particularly the Malay speakers, to pronounce these letters correctly. Hence, in this thesis, noise reduction and consonants recognition are conducted among the Malay speakers. The Malay race has been chosen due to the high usage of the Arabic language for reciting Al-Quran. Generally, the study is divided into two parts, namely, the study of noise reduction and consonant recognition. First, two noise removal methods were developed. The first method is based on combining Negative function with Gamma correction function. The second noise reduction method is addressed by utilising 2D Gabor filter. Furthermore, the consonant study was conducted based on Automatic Speech Recognition (ASR) system concept. The ASR composes of feature extraction stage followed by speech recognition. On the other hand, the feature extraction was implemented by investigating three different methods, namely, Mel-Frequency Cepstrum Coefficients (MFCC), Linear Prediction Coefficients (LPC) and Perceptual Linear Prediction (PLP)…
format Book Section
author Almisreb, Ali Abd
author_facet Almisreb, Ali Abd
author_sort Almisreb, Ali Abd
title Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb
title_short Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb
title_full Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb
title_fullStr Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb
title_full_unstemmed Consonants recognition and noise reduction for Arabic phonemes based Malay speakers / Ali Abd Almisreb
title_sort consonants recognition and noise reduction for arabic phonemes based malay speakers / ali abd almisreb
publisher Institute of Graduate Studies, UiTM
publishDate 2016
url http://ir.uitm.edu.my/id/eprint/19629/1/ABS_ALI%20ABD%20ALMISREB%20TDRA%20VOL%209%20IGS%2016.pdf
http://ir.uitm.edu.my/id/eprint/19629/
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