@inproceedings{ca6506688a5742e79b08d6e3c0948aa5,
title = "BIT's system for the AutoSimTrans 2020",
abstract = "This paper describes our machine translation systems for the streaming Chinese-to- English translation task of AutoSimTrans 2020. We present a sentence length based method and a sentence boundary detection model based method for the streaming input segmentation. Experimental results of the transcription and the ASR output translation on the development data sets show that the translation system with the detection model based method outperforms the one with the length based method in BLEU score by 1.19 and 0.99 respectively under similar or better latency.",
author = "Minqin Li and Haodong Cheng and Yuanjie Wang and Sijia Zhang and Liting Wu and Yuhang Guo",
note = "Publisher Copyright: {\textcopyright} 2020 Association for Computational Linguistics.; 1st Workshop on Automatic Simultaneous Translation, AutoSimTrans 2020 at the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 ; Conference date: 10-07-2020",
year = "2020",
language = "English",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "37--44",
booktitle = "ACL 2020 - Workshop on Automatic Simultaneous Translation Challenges, Recent Advances, and Future Directions, Proceedings of the Workshop",
address = "United States",
}