A Chinese-Japanese Parallel Corpus for Neural Machine Translation Based on Web-Crawled News Data
Current research on Japanese-Chinese parallel corpora is limited, particularly in the general field, and existing corpora are often small in scale. The purpose of this study is to fill this gap by constructing a large scale of Chinese-Japanese parallel corpus, sourced from web-crawled online news data. We also evaluated the quality of the constructed Web Crawled Corpus of Japanese and Chinese News (WCC-JCN), which comprised approximately 660K Chinese-Japanese sentence pairs, by calculating its BLEU scores and comparing it with the established ASPEC-JC corpus. The WCC-JCN is made freely available for download, provided it is used for research purposes only, thereby contributing to future research in this area.
Authors
- Tadahiro Matsumoto (ORCID: https://orcid.org/0009-0002-4106-1099)
- Jinyi Zhang (ORCID: https://orcid.org/0000-0002-9813-217X)
- Ye Tian (ORCID: https://orcid.org/0000-0002-0981-6677)
- Zhonghui Gao (ORCID: https://orcid.org/0009-0003-4777-4505)
Institutions
- Shenyang Ligong University (CN)
- Gifu University (JP)
Publication Details
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/spic62469.2024.10691539
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shenyang Ligong University
- China Scholarship Council