In this paper, automatic Arabic character diacritization is more accurately achieved using deep neural networks. Actually, though diacritic signs represent short vowels and/or indicate gemination on consonants, they are omitted in modern standard Arabic (MSA). However, most speech processing applications like speech synthesis and machine translation need such marks to convey the right meaning. Therefore in this work, automatic diacritization accuracy is enhanced using feedforward DNN. The results show that using more significant and Arabic-specific input features increases the prediction accuracy of diacritic signs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.