AraSpell: A Deep Learning Approach for Arabic Spelling Correction

arXiv:2405.06981v1 Announce Type: new
Abstract: Spelling correction is the task of identifying spelling mistakes, typos, and grammatical mistakes in a given text and correcting them according to their context and grammatical structure. This work introduces "AraSpell," a framework for Arabic spelling correction using different seq2seq model architectures such as Recurrent Neural Network (RNN) and Transformer with artificial data generation for error injection, trained on more than 6.9 Million Arabic sentences. Thorough experimental studies provide empirical evidence of the effectiveness of …

abstract arabic architectures arxiv context cs.ai cs.cl deep learning framework mistakes seq2seq text them type typos work