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