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arXiv · 2311.17492

Mergen: The First Manchu-Korean Machine Translation Model Trained on Augmented Data

Jean Seo·Sungjoo Byun·Minha Kang·Sangah Lee
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Abstract

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.

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Jean Seo, Sungjoo Byun, Minha Kang, Sangah Lee. 2023-11-29. Mergen: The First Manchu-Korean Machine Translation Model Trained on Augmented Data. https://arxiv.org/abs/2311.17492

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