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Journal of Intelligent Systems and Internet of Things
Volume 1 , Issue 2, PP: 72-79 , 2020 | Cite this article as | XML | Html |PDF


Handling within-word and cross-word pronunciation variation for Arabic speech recognition (knowledge-based approach)

Authors Names :   Ibrahim El-Henawy   1 *     Marwa Abo-Elazm   2  

1  Affiliation :  Computer Science Department, Faculty of Computers and Informatics, Zagazig University, Egypt

    Email :  henawy2000@yahoo.com

2  Affiliation :  Computer Science Department, Faculty of Computers and Informatics, Zagazig University, Egypt

    Email :  marwa_abdella@yahoo.com

Doi   :   https://doi.org/10.54216/JISIoT.010202

Abstract :

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.

Keywords :

Speech Recognition Systems , Arabic Language , Phonetic Dictionary , pronunciation variations

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Cite this Article as :
Ibrahim El-Henawy , Marwa Abo-Elazm, Handling within-word and cross-word pronunciation variation for Arabic speech recognition (knowledge-based approach), Journal of Intelligent Systems and Internet of Things, Vol. 1 , No. 2 , (2020) : 72-79 (Doi   :  https://doi.org/10.54216/JISIoT.010202)