Amharic-Khimtagne Bi-directional Machine Translation  Using Deep Learning

Adane, Kasie Chekole

dc.contributor.author	Adane, Kasie Chekole
dc.date.accessioned	2024-04-19T08:25:46Z
dc.date.available	2024-04-19T08:25:46Z
dc.date.issued	2023-07
dc.identifier.uri	http://ir.bdu.edu.et/handle/123456789/15768
dc.description.abstract	r Amharic-Khimtagne and Khimtagne-Amharic translations, respectively. The main limitation of this research is the lack of sufficient datasets to conduct an entire experiment. Therefore, it is necessary to collect parallel corpora to facilitate further research in this field. Keywords: Amharic-Khimtagne Machine Translation, Bi-Directioanl Machine Translation, NLP, NMT, Deep Learning, LSTM, LSTM with attention, CNN with attention, Transformers.	en_US
dc.language.iso	en_US	en_US
dc.subject	Software Engineering	en_US
dc.title	Amharic-Khimtagne Bi-directional Machine Translation Using Deep Learning	en_US
dc.type	Thesis	en_US