Natural Language Processing and Its Challenges on Omotic Language Group of Ethiopia

Abstract

This article reviews Natural Language Processing (NLP) and its challenge on Omotic language groups. All technological achievements are partially fuelled by the recent developments in NLP. NPL is one of component of an artificial intelligence (AI) and offers the facility to the companies that need to analyze their reliable business data. However, there are many challenges that tackle the effectiveness of NLP applications on Omotic language groups (Ometo) of Ethiopia. These challenges are irregularity of the words, stop word identification problem, compounding and languages ‘digital data resource limitation. Thus, this study opens the room to the upcoming researchers to further investigate the NLP application on these language groups.