Author, Institution: Senait Gebremichael Tesfagergish, Kaunas University of Technology
Science area, field of science: Technological Sciences, Informatics Engineering, T007
Research supervisor: Prof. Dr. Robertas Damaševičius (Kaunas University of Technology, Technological Sciences, Informatics Engineering, T007)
Research consultant: Prof. Dr. Jurgita Kapočiūtė-Dzikienė (Vytautas Magnus University, Natural Sciences, Informatics, N009)
Dissertation Defence Board of Informatics Engineering Science Field:
Prof. Dr. Tomas Skersys (Kaunas University of Technology, Technological Sciences, Informatics Engineering, T007) – chairperson
Prof. Dr. Nikolaj Goranin (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering, T007)
Dr. Gražina Korvel (Vilnius University, Technological Sciences, Informatics
Engineering, T007)
Prof. Dr. Sanda Martinčic-Ipšic (University of Rijeka, Croatia, Technological
Sciences, Informatics Engineering, T007)
Prof. Dr. Simona Ramanauskaitė (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering, T007)
Dissertation defence meeting will be at Rectorate Hall of Kaunas University of Technology (K. Donelaičio 73–402, Kaunas)
The doctoral dissertation is available at the library of Kaunas University of Technology (Gedimino g. 50, Kaunas) and on the internet: S. Gebremichael Tesfagergish el. dissertation.pdf
© S. Gebremichael Tesfagergish, 2025 “The text of the thesis may not be copied, distributed, published, made public, including by making it publicly available on computer networks (Internet), reproduced in any form or by any means, including, but not limited to, electronic, mechanical or other means. Pursuant to Article 25(1) of the Law on Copyright and Related Rights of the Republic of Lithuania, a person with a disability who has difficulties in reading a document of a thesis published on the Internet, and insofar as this is justified by a particular disability, shall request that the document be made available in an alternative form by e-mail to doktorantura@ktu.lt.”
Annotation: This dissertation explores AI-driven solutions to advance Natural Language Processing (NLP) for low-resource languages, with a primary focus on Amharic. While high-resource languages benefit from vast linguistic resources and tools, languages like Amharic lack annotated datasets and computational frameworks, limiting the development of core NLP applications. This research addresses those challenges by developing classification models, implementing transformer-based embeddings, and applying innovative data augmentation methods. It also integrates Explainable AI (XAI) techniques to enhance transparency and trust in model predictions. Key applications examined include sentiment analysis, intent recognition, cyberbullying detection, deepfake recognition, and part-of-speech tagging. The study demonstrates that tailored NLP methods not only improve performance for Amharic but can also be generalized to other underrepresented languages. Overall, this work contributes to the inclusivity and robustness of AI technologies in linguistically diverse digital spaces.