Avatar-based system for transform continuous Arabic speech into Arabic sign language
Hassan, H., saad, E., Ahmed, S., sayed, S., Nasser, A., Shaheen, M. (2017). Avatar-based system for transform continuous Arabic speech into Arabic sign language. EKB Journal Management System, 2(Second International Undergraduate Research Conference, IUGRC), 37-37. doi: 10.21608/iugrc.2017.90639
Hossam Hassan; Eslam saad; Sally Ahmed; Sarah sayed; Aya Nasser; Masoud Shaheen. "Avatar-based system for transform continuous Arabic speech into Arabic sign language". EKB Journal Management System, 2, Second International Undergraduate Research Conference, IUGRC, 2017, 37-37. doi: 10.21608/iugrc.2017.90639
Hassan, H., saad, E., Ahmed, S., sayed, S., Nasser, A., Shaheen, M. (2017). 'Avatar-based system for transform continuous Arabic speech into Arabic sign language', EKB Journal Management System, 2(Second International Undergraduate Research Conference, IUGRC), pp. 37-37. doi: 10.21608/iugrc.2017.90639
Hassan, H., saad, E., Ahmed, S., sayed, S., Nasser, A., Shaheen, M. Avatar-based system for transform continuous Arabic speech into Arabic sign language. EKB Journal Management System, 2017; 2(Second International Undergraduate Research Conference, IUGRC): 37-37. doi: 10.21608/iugrc.2017.90639

Avatar-based system for transform continuous Arabic speech into Arabic sign language

The International Undergraduate Research Conference
Article 23, Volume 2, Second International Undergraduate Research Conference, IUGRC, 2017, Page 37-37  XML PDF (458.85 K)
Document Type: Original Article
DOI: 10.21608/iugrc.2017.90639
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Authors
Hossam Hassan1; Eslam saad1; Sally Ahmed1; Sarah sayed1; Aya Nasser1; Masoud Shaheen2
1Fayoum university, Egypt.
2Assistant Professor, Fayoum, Egypt,
Abstract
Arabic language is the fifth most spoken language in the world, 10% from Arabic speakers are suffering from disability to hear. So the need for translating Arabic speech to sign language is increasing rapidly. This paper presents an automatic translation system that translates continuous Arabic speech to Arabic sign language. This system performs the Arabic speech recognition using a framework that we also developed, based on Carnegie Mellon University Sphinx (CMU Sphinx), hidden mark of model (HMM) and Mel-frequency Ceptral Coefficient Technique (MFCC). In addition to using computer graphics to display the sign language.
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