Workineh Tesema and Duresa Tamirat
Afan Oromo is a member of the Cushitic branch of the Afro-Asiatic language family, which was the third most widely spoken language in Africa, after Hausa and Arabic. Its original homeland is an area that includes much of what is today Ethiopia and some parts of East African countries. Afan Oromo uses a Latin script which consists of thirty three basic letters, of which five are vowels, twenty-four are consonants, out of which seven are paired letters and fall together (a combination of two consonant characters such as ‘CH’, ‘DH’, ‘NY’, ‘SH’, ‘TS’ ). The idea behind this work is to open a chance to obtain computer software and file editing tool in Afan Oromo language. In order to develop this tool, unsupervised machine learning which was trained on unlabeled corpus. The training data were collected from government media, cultural, historical, sport news, political, and economical documents of Afan Oromo users were used. Once, the trained data was collected based on language structure N-gram algorithms (namely Unigram, Bigram, Trigram & Fourth Gram) were applied. Hence, Afan Oromo is one of the limited resources (small dataset) for training it restricted to use Unigram, Bigram and Trigram. Therefore, this work presents how we improve word entry information and input method as an assistive technology. Hence, this language uses double vowels (in this case waadaa) it needs integrated and independent file editor for native users of the language. As the developed system shows that it makes easy to text entry and improve the way to input files to computers. Finally, this work was brought the Oromo population, which is the first largest population of Ethiopian populations to get access the technology by their mother tongue language. The finding of the study was argued that the file editor indispensable to use technology by own language and especially for disable and typist to edit own file.
