Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT 2019 2019 Handling within-word and cross-word pronunciation variation for Arabic speech recognition (knowledge-based approach) Computer Science Department, Faculty of Computers and Informatics, Zagazig University, Egypt Ibrahim El-Henawy, Marwa Abo* Abo-Elazm* Arabic is one of the phonetically complex languages, and the creation of accurate speech recognition system is a challengeable task. Phonetic dictionary is essential component in automatic speech recognition system (ASR). The pronunciation variations in Arabic are tangible and are investigated widely using data driven approach or knowledge based approach. The phonological rules are used to get the pronunciation of each word accurately to reduce the mismatch between the actual phoneme representation of the spoken words and ASR dictionary. Several studies in Arabic ASR system are conducted using different number of phonological rules. In this paper we focus on those rule that handle within-word pronunciation variation and cross-word pronunciation variation. The experimental results indicate that handling within-word pronunciation variation using phonological rule doesn’t enhance the recognition performance, but  using these rules to  handle cross-word variation provide a good performance. 2021 2021 72 79 10.5281/zenodo.3629745