Journal of Intelligent Systems and Internet of Things
JISIoT
2690-6791
2769-786X
10.54216/JISIoT
https://www.americaspg.com/journals/show/5
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
admin
admin
Computer Science Department, Faculty of Computers and Informatics, Zagazig University, Egypt
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.
2020
2020
72
79
10.54216/JISIoT.010202
https://www.americaspg.com/articleinfo/18/show/5