- 2 November 2023
- Current projects
The general objective of the project is to develop a multilingual machine translation prototype capable of detecting and mitigating gender bias for low-resource languages.
AI systems copy and reinforce existing social biases, a problem now widely recognized and studied. But current research on gender bias in natural language processing (NLP) definitely points to a solution.
Gender biases in AI applications such as machine translation (MT) are common and should be carefully considered when developing such applications.
In this project, we propose to develop MT prototype capable of detecting and mitigating gender bias. Since the target languages Amharic, Ge'ez and Awign fall into the category of resource-limited languages, we will use transfer learning to take advantage of available resource-rich languages such as English.
The project is relevant and current in addressing the challenges of the language barrier between different local communities as well as the issue of gender bias in MT datasets.
Successful implementation of the project could have the potential to address these challenges inside and outside Ethiopia, particularly in sub-Saharan Africa.
Project leader’s name
Walelign Tewabe Sewunetie Walelign Tewabe Sewunetie has a degree in computer science and over 14 years' corporate experience in teaching, consulting, research and projects. He graduated from Arba Minch University Institute of Technology with a Master's degree in Computer Science. Walelign is a dynamic young academic with a wide range of research interests. His research interests include computer science, AI, NLP, intelligent tutoring systems, software engineering and more. His doctoral research topic is the design and development of automatic question generation models. He has published more than 10 research papers in reputed international journals and conferences indexed by Scopus and IEEE, as well as in many others. He has worked on many important projects throughout his career. Among these, "Designing Machine Learning Method for Software Project Effort Prediction" was funded by Debre Markos University.
The other team members
Zewdie Mossie has been with Debre Markos University for 15 years. He is currently Dean of the Debre Markos University Institute of Technology and Assistant Professor of Computer Science. He has taught a variety of subjects, including computer programming (in C++ and Python), database management, computer and information security, IT project management, big data analysis, and scientific research and writing. His research interests include natural language processing, big data analysis, social network data analysis, human data mining and information and network security. He has published articles in journals and contributed to several conferences on topics related to information technology and computer science. In addition, he has participated in numerous projects and is currently working on the following: "Design and development of a mobile text-to-speech system in Amharic for visually impaired and blind students".
Yaregal Assabie is Associate Professor at Addis Ababa University and Chairman of the Computer Science Department. In 2009, he obtained a PhD in Electrical Engineering (with a subfield in Computer Systems) from Chalmers University of Technology, Gothenburg, Sweden.
He obtained a Master's degree in Information Science from Addis Ababa University (AAU), Addis Ababa, in 2002, and a Bachelor's degree in Computer Science from Addis Ababa University (AAU), Addis Ababa, in 1998. He has held various positions in different projects and committees. He has taught various courses such as natural language processing, digital image processing, deep learning and distributed systems at postgraduate level. Yaregal Assabie has also carried out five research and development projects funded by the Ministry of Science and Technology, Addis Ababa University and the Ministry of Communication and Information Technology.
Fentanesh Nibret a Project team member, worked as an assistant professor at Bahir Dar University, Ethiopia. She is a public health researcher who has worked on gender-based violence against women, women’s autonomy, gender inequality, and adverse health outcomes. She published in different journals on gender and health-related topics like Decision-making autonomy of women and other factors of anemia among married women in Ethiopia, Associations of early marriage and early childbearing with anemia among adolescent girls in Ethiopia, Women’s autonomy, and maternal healthcare service utilization in Ethiopia. She has a better understanding of gender and related topics that can help to achieve one of the objectives of gender bias AI. Her upcoming research interests include using digital technology to provide information to women to improve their health.
Yenework Belayneh has been employed for the past 6 years at Injibara University, Ethiopia. She presently holds the position of Library Director at Injibara University, and she also worked as the Information Technology department head. She taught various subjects including Emerging Technologies, fundamentals of Programming, Fundamental Programming, Data communication and computer networks, Network Design, System Administration, and Data structure and Algorithms. Her research focuses on natural language processing and gender-related applications in women’s life. She also participated in conference hosting and reviewing. She is currently working on the following projects : AUTOMATIC speech recognition SYSTEM for AWNGI (አውጚ）language.
Debre Markos University (DMU) is a public research university located in Debre Markos, Ethiopia. It was established in January 2005. Two years later, DMU began the process of teaching and learning with 760 regular students, 53 academic staff and 34 supports staff, as well as 21 contract staff, and its name was officially declared Debre Markos University. DMU currently has 51 undergraduates, 47 postgraduates and 2 PhD programs in regular, continuing and distance education. DMU has provided competitive and competent graduates to national and international organizations at 11 undergraduate and postgraduate graduation ceremonies. In addition, 126 doctors graduated in three cycles. The university currently has three campuses, five colleges, two schools and three institutes.
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