Short bio : Dr. Soudi is a full Professor at ENSMR-Rabat, Morocco. He has made outstanding contributions to the field of Natural Language Processing and Assistive Technology for the benefit of both the Deaf and Hearing persons. Dr. Soudi has been awarded several international research awards, such as the German-African Innovation Incentive Prize (2020), two PEER Science Awards (2012;2014)-Partnership for Enhanced Engagement in Research- from the USA National Academies of Sciences, and the Literacy Innovation Award from USAID, World Vision and Australian Aid (2015). Dr. Soudi was a Fulbright Scholar at Carnegie Mellon University (USA) and Alexander von Humboldt Senior research fellow at several German universities. He has published several books, chapters and papers in the area of Natural Language Processing. Dr. Soudi has chaired several international and national conferences in the area of human language technologies. Dr. Soudi has also been very active in establishing international networks for scientific cooperation. He was Founding President of the Maghreb-Alexander von Humboldt Alumni Association, founding member of the Fulbright Alumni Association, and has been Advisory Board member of the Arab-German Young Academy of Sciences and Humanities.

Accessible Assistance Technology for Improved Communication between Deaf and Hearing People

Abstract:The Deaf and Hard of Hearing (D/HoH) often feel marginalized because of the lack of :

• access to information in sign language (SL) and
• interpreters, especially during crisis and emergency situations. Because of the lack of communication, D/HoH people are subject to misunderstanding and discrimination and often live in somewhat secluded environments. The consequences to Deaf’s welfare, safety, health, life opportunities, and full enjoyment of their rights are incalculable.

In this presentation, I will introduce a software system that enables D/DoH to:

• Interact with healthcare personnel and other service providers using a user friendly platform; and
• Translate information in real time, including the generation of signs using avatar technology

The translation engine is a reversible system that translates in both directions: spoken language to SL and SL to spoken language. The system offers several input and output options: 1. voice, 2. Text and 3. a user-friendly sign language platform that is based on a notation system specific to sign languages. The notation system includes both manual and non-manual markers. With regard to sign language synthesis, our technology also offers the possibility to generate sentences using a virtual signing avatar

Brief Bibliography : Mohammed Al-Sarem is an associate professor, a fellow of the higher education academy (FHEA), UK, a certified Google data scientist, and a researcher with +10 years of experience teaching courses on undergraduate and postgraduate levels. His research interests include Artificial Intelligence, Big Data Analytics, Natural Language Processing (NLP), Social Network Analysis, Educational Data Mining, and Machine Learning/ Deep Learning. He published over +35 articles in ISI journals and about 34 conference papers. In addition, he managed and organized many international conferences. He received many grants/funding from local and international parties.

Current Research Interests:

Natural language processing; Social network analysis; Machine learning/ Deep Learning, Structured prediction, Neural networks; Data Science, Data Analysis; Information extraction; (Educational) Data mining; Statistical data analysis. The translation engine is a reversible system that translates in both directions: spoken language to SL and SL to spoken language. The system offers several input and output options: 1. voice, 2. Text and 3. a user-friendly sign language platform that is based on a notation system specific to sign languages. The notation system includes both manual and non-manual markers. With regard to sign language synthesis, our technology also offers the possibility to generate sentences using a virtual signing avatar.

• Google Scholar : h-index (21) i10-index (31), Citation No. (1272)
• Scopus : h-index (16), Citation No. (803)
• WoS : h-index (13), Citation No.: (495)
• Research Gate : h-index (17), Score (28.54), Citation (1097)