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

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.


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)…


Item Type: Book Section
CreatorsEmail / ID. Num
Almisreb, Ali AbdUNSPECIFIED
Subjects: L Education > LB Theory and practice of education > Higher Education > Dissertations, Academic. Preparation of theses > Malaysia
P Language and Literature > P Philology. Linguistics > Language. Linguistic theory. Comparative grammar
Divisions: Universiti Teknologi MARA, Shah Alam > Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS)
Series Name: IGS Biannual Publication
Volume: 9
Number: 9
Item ID: 19629
Uncontrolled Keywords: Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; Consonants recognition



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