@inproceedings{22a77c69255646cb860b527bb69c8652,
title = "BIT's system for AutoSimTrans 2021",
abstract = "In this paper we introduce our Chinese-English simultaneous translation system participating in AutoSimTrans 2021. In simultaneous translation, translation quality and latency are both important. In order to reduce the translation latency, we cut the streaming-input source sentence into segments and translate the segments before the full sentence is received. In order to obtain high-quality translations, we pre-train a translation model with adequate corpus and fine-tune the model with domain adaptation and sentence length adaptation. The experimental results on the development dataset show that our system performs better than the baseline system.",
author = "Mengge Liu and Shuoying Chen and Minqin Li and Zhipeng Wang and Yuhang Guo",
note = "Publisher Copyright: {\textcopyright}2021 Association for Computational Linguistics; 2nd Workshop on Automatic Simultaneous Translation Challenges, Recent Advances, and Future Directions, AutoSimTrans 2021 ; Conference date: 10-06-2021",
year = "2021",
language = "English",
series = "Proceedings of the 2nd Workshop on Automatic Simultaneous Translation Challenges, Recent Advances, and Future Directions, AutoSimTrans 2021",
publisher = "Association for Computational Linguistics (ACL)",
pages = "12--18",
editor = "Hua Wu and Colin Cherry and Liang Huang and Zhongjun He and Qun Liu and Maha Elbayad and Mark Liberman and Haifeng Wang and Mingbo Ma and Ruiqing Zhang",
booktitle = "Proceedings of the 2nd Workshop on Automatic Simultaneous Translation Challenges, Recent Advances, and Future Directions, AutoSimTrans 2021",
address = "United States",
}