  The Manchu language, with its roots in the historical Manchurian region of
Northeast China, is now facing a critical threat of extinction, as there are
very few speakers left. In our efforts to safeguard the Manchu language, we
introduce Mergen, the first-ever attempt at a Manchu-Korean Machine Translation
(MT) model. To develop this model, we utilize valuable resources such as the
Manwen Laodang(a historical book) and a Manchu-Korean dictionary. Due to the
scarcity of a Manchu-Korean parallel dataset, we expand our data by employing
word replacement guided by GloVe embeddings, trained on both monolingual and
parallel texts. Our approach is built around an encoder-decoder neural machine
translation model, incorporating a bi-directional Gated Recurrent Unit (GRU)
layer. The experiments have yielded promising results, showcasing a significant
enhancement in Manchu-Korean translation, with a remarkable 20-30 point
increase in the BLEU score.
