Amharic-Awngi Machine Translation: An Experiment Using Statistical Approach - Mekonnen, Habtamu (International Journal of Computer Sciences and Engineering, 2019)
Nowadays, there are huge amount of texts written in Amharic language. Theses texts, documents and related Amharic literatures are usable for individuals, who can read, hear and understand Only Amharic languages. But In Ethiopia, there are many individuals who cannot hear and understand any text and literature written in Amharic language unless there is parallel translation in language they are good. These documents need to be translated to Awngi to provide valuable information for Awngi language speakers. To conduct the research, the corpus was collected from Amharic texts, Mass Media Agency and Bible. We used minimum of 1500 simple sentences, 1000 compound and 1000 complex sentences and maximum of 5000 sentences for each sentences type in order to train the system. We used 9:1 ratio for training and testing respectively. For language model we used minimum of 5700 and maximum of 14491 monolingual sentence of Awngi language. To do the system, we used Moses for Mere Mortal for translation process, MGIZA++ for alignment and IRSTLM for language model. Experimental results showed that better performance of 37% BLUE score was registered using complex sentences. In Amharic language, a word in sentences can have more than one meaning. While translating, the challenge of this study was not translating the meaning of the given sentences according to the context. But this study has not solved that challenge which needs further study to show all meanings of word depending on the context properly.