In this work, we studied the possibility of the detection of Parkinson disease from the voice signal variation patterns. We further developed a model using the voice signal features and evaluated its effectiveness. From the experimental results, we conclude that the recognition rate of KNN comes out to be 80%, but, with Naïve Bayes the classification has the highest recognition rate which is 93.3%. So we can say that it is better for recognition. The developed system was confirmed that voice signal measurement is a practical and useful screening test to estimate whether patients have PD or not

Few methods have been focused on presenting automatic methods for pronunciation of Arabic words. In this work, we studied the possibility of pronunciation learning of Arabic definite article. The proposed approach will have major benefits on learning to read Arabic outcomeseither to speakers or non-speakers of Arabic language.