| 研究実績の概要 |
Our research focused on enhancing machine translation for low-resource scenarios such as translation between Asian languages and English, and translation in specific domains such as the educational domain. To achieve this, we propose to 1) create bilingual corpora, mainly in the first year, for the low-resource domain and 2) optimize the subword segmentation information during the encoding phase in the second year and the decoding phase in the last year.
As for the publications, during the last year, there were 3 first-authored journal papers and 1 conference paper published or submitted. Over the past three years, there have been 4 journal papers and 9 international conference papers, including co-authored papers. Additionally, one patent application is underway.
This research has significantly improved the translation quality for low-resource scenarios. Through experiments, we found that the quality score measured by BLEU is improved by more than 3 points.
The low-resource translation system is indispensable for cross-cultural communication in international events such as EXPO 2025. With our approach, we can make the translation system more practical for participants who speak low-resource languages.
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