safaa omer | Sudan university of Science and technology (original) (raw)
Address: Saudi Arabia
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INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY, 2021
Visual speech information plays an important role in lip-reading under noisy conditions or for li... more Visual speech information plays an important role in lip-reading under noisy conditions or for listeners with a hearing impairment. Correct utterances to read Quran for beginners, there are rules of utterances to learn Quran and we need a software system to tell us if we utter correctly. For that, we built lip-reading model, the model localizes the lips efficiently.
We present in this study a classification model for some al-tajweed rules as we depended on Machine Learning - Cascade Object Detector (Viola-Jones Algorithm), HOG features, a multiclass SVM classifier and Aggregate Channel Features (ACF) object detector for features extraction. We uses Matlab to train a classifiers using a pre-trained convolutional neural network (CNN) for classifying images from the video stream of four different Rules of Holy Quran Allah Elevating (mufakhum), Allah Lowering (moureqeq), sunny لام and moonyلام . CNN acquires multiple convolutional filters, used to extract visual features essential for recognizing phoneme. CNNs produce
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY, 2021
Visual speech information plays an important role in lip-reading under noisy conditions or for li... more Visual speech information plays an important role in lip-reading under noisy conditions or for listeners with a hearing impairment. Correct utterances to read Quran for beginners, there are rules of utterances to learn Quran and we need a software system to tell us if we utter correctly. For that, we built lip-reading model, the model localizes the lips efficiently.
We present in this study a classification model for some al-tajweed rules as we depended on Machine Learning - Cascade Object Detector (Viola-Jones Algorithm), HOG features, a multiclass SVM classifier and Aggregate Channel Features (ACF) object detector for features extraction. We uses Matlab to train a classifiers using a pre-trained convolutional neural network (CNN) for classifying images from the video stream of four different Rules of Holy Quran Allah Elevating (mufakhum), Allah Lowering (moureqeq), sunny لام and moonyلام . CNN acquires multiple convolutional filters, used to extract visual features essential for recognizing phoneme. CNNs produce