English-Amharic Document Translation Using Hybrid Approach

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Addis Ababa University


Machine Translation (MT) is a sub field of Natural Language Processing (NLP) that investigates the use of computer software to translate text or speech from one natural language to another. Recently, in Ethiopia English documents are translated to Amharic using human translators, because of the absence of Automated Translation System. Due to this, the process of document translation is so expensive, challenging, unsecured and time consuming. To solve those problems statistical based approaches were proposed to translate English to Amharic. However, the approaches have accuracy and understandability issues. In order to solve these problems we propose a Hybrid approach machine translation (HMT) system that combines Statistical and Rule Based Machine Translation approaches. In this case using the hybrid approach achieved better accuracy and found to be advanced for English - Amharic machine translation system over SMT approach. The proposed hybrid approach achieved 15% and 20% accuracy improvement for simple and complex sentences over statistical machine translation approach. This study also identified preprocessing the inputs of SMT is more suitable to improve accuracy for complex sentences while post-processing the outputs of SMT is more suitable for simple sentences.



Machine Translation, SMT, RBMT, HMT