@article{(Open Science Index):https://publications.waset.org/pdf/6086, title = {On Developing an Automatic Speech Recognition System for Standard Arabic Language}, author = {R. Walha and F. Drira and H. El-Abed and A. M. Alimi}, country = {}, institution = {}, abstract = {The Automatic Speech Recognition (ASR) applied to Arabic language is a challenging task. This is mainly related to the language specificities which make the researchers facing multiple difficulties such as the insufficient linguistic resources and the very limited number of available transcribed Arabic speech corpora. In this paper, we are interested in the development of a HMM-based ASR system for Standard Arabic (SA) language. Our fundamental research goal is to select the most appropriate acoustic parameters describing each audio frame, acoustic models and speech recognition unit. To achieve this purpose, we analyze the effect of varying frame windowing (size and period), acoustic parameter number resulting from features extraction methods traditionally used in ASR, speech recognition unit, Gaussian number per HMM state and number of embedded re-estimations of the Baum-Welch Algorithm. To evaluate the proposed ASR system, a multi-speaker SA connected-digits corpus is collected, transcribed and used throughout all experiments. A further evaluation is conducted on a speaker-independent continue SA speech corpus. The phonemes recognition rate is 94.02% which is relatively high when comparing it with another ASR system evaluated on the same corpus.}, journal = {International Journal of Electrical and Computer Engineering}, volume = {6}, number = {10}, year = {2012}, pages = {1138 - 1143}, ee = {https://publications.waset.org/pdf/6086}, url = {https://publications.waset.org/vol/70}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 70, 2012}, }