Admasu Yonas (PhD)Abdela Woinshet (W/ro)Berhanu SolomonLisanu Kibur2018-11-162023-11-182018-11-162023-11-182002-06http://etd.aau.edu.et/handle/12345678/14360Natural Language processing plays a significant role in increasing computers’ capability to understand natural languages. Morphological synthesis is one aspect of the task of understanding natural language, the language by which most human knowledge is recorded. Morphological synthesis or generation is a process of returning one or more surface forms from a sequence of underlying (lexical) forms. Morphological synthesis systems are used as components in many applications, including machine translation, spell-check, speech recognition, dictionary (lexicon) compilation, POS tagging, morphological analysis, conversational systems, automatic sentence construction and many others. Today, synthesizers of different kinds have been developed for languages that have relatively wider use internationally. The same cannot be said for Amharic, the working language of the Federal Government of Ethiopia, and one of the major languages of the country (Bender, 1976). This study is, thus, an attempt to develop a prototype automatic morphological synthesizer for Amharic, specifically for perfective verb forms. In this study, algorithms that take into consideration the morphological properties of Amharic are developed from scratch and applied, as there are no previous such attempts. The study adopts the combination of rule-based and neural network approaches to design and develop a prototype, referred as AmharicMorphologicalSynthesizer. The rule-based approach generates all the roots successfully where as the neural network predicts the type of roots in the test data set with an accuracy of 81.48%. For a new case consisting of 14 roots the neural network identifies type A perfective verb forms with an accuracy of 80%, type B perfective verb forms with accuracy of 25% and that of type C perfective verb forms with an accuracy of 100%. The thesis, in short, describes processes of automated morphological synthesis from manually synthesizing words to developing a prototype and conducting an experiment with it. The result obtained using the small manually constructed root table will encourage the undertaking of further research in the area, especially with the aim of developing a full-fledged Amharic morphological synthesizer.enNatural language processingThesis