Abstract
Aiming at facilitating the research on quality estimation (QE) and automatic post-editing (APE) of machine translation (MT) outputs, especially for those among Asian languages, we have created new datasets for Japanese to English, Chinese, and Korean translations. As the source text, actual utterances in Japanese were extracted from the log data of our speech translation service. MT outputs were then given by phrase-based statistical MT systems. Finally, human evaluators were employed to grade the quality of MT outputs and to post-edit them. This paper describes the characteristics of the created datasets and reports on our benchmarking experiments on word-level QE, sentence-level QE, and APE conducted using the created datasets.- Anthology ID:
- W17-5705
- Volume:
- Proceedings of the 4th Workshop on Asian Translation (WAT2017)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Venue:
- WAT
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 79–88
- Language:
- URL:
- https://aclanthology.org/W17-5705
- DOI:
- Cite (ACL):
- Atsushi Fujita and Eiichiro Sumita. 2017. Japanese to English/Chinese/Korean Datasets for Translation Quality Estimation and Automatic Post-Editing. In Proceedings of the 4th Workshop on Asian Translation (WAT2017), pages 79–88, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- Japanese to English/Chinese/Korean Datasets for Translation Quality Estimation and Automatic Post-Editing (Fujita & Sumita, WAT 2017)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/W17-5705.pdf