Artificial Intelligence Model to Detect and Classify Arabic Dialects

The Arabic Dialect (AD) detection method involves analyzing the matching sound wave for various characteristics that identify speaker’s dialect. Among these features are accent, intonation, stress, vowel length, type, and other acoustic characteristics. Data from different speakers of dialects is usually used in training machine learning algorithms. Based on this data, an algorithm created to accurately can be detected classified using several models techniques available literature. Various have been proposed perspectives. Therefore, paper discussed studies about AD building understanding conceptual deep model detect classify dialects. captured semantic, syntactic, phonological Convolutional Neural Networks (CNNs) Recurrent (RNNs). consists six stages: Natural Language Processing (NLP) stage, feature engineering techniques, neural networks, language models, optimization evaluation techniques. Each stage has AD. accuracy capability will performed future work.