A Bi-directional Ge’ez-Amharic Neural Machine Translation: A Deep Learning Approach
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Currently, youth and researchers are interested to learn and involve in research areas of Ge’ez and Amharic manuscripts. This thesis, therefore, aims to demonstrate the capabilities of deep learning algorithms on MT tasks for those morphologically rich languages.
A bi-directional text-based Ge’ez-Amharic MT was tested on two main different deep learning models viz. Seq2Seq with attention, and Transformer.
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£27.18
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