Arabic Automatic Segmentation System and its Application for Arabic Speech Recognition System
M. Nofal, Esam Abdel‐Raheem, H. El Henawy, N.S. Abdel Kader · 2006
The paper presents an Arabic automatic segmentation system to be utilized in the development of an Arabic speech recognition system. The automatic segmentation system is used to label a speech database system that is used in the training of continuous, phoneme based speaker independent Hidden Markov Models. Our experiments showed that 7.8 % of the phoneme boundaries of automatic segmented data deviate from those that were manually segmented more than 30 milliseconds while 0.78 % deviate more than 70 milliseconds. Our experiments showed also that automatic segmentation led to improvement in speech recognition accuracy of 0.49 % for a 306 words bigram language model test and 0.14% for 1340 words bigram model.