Interactive machine translation (IMT) has emerged as a progression of the computer-aided translation paradigm, where the machine translation system and the human translator collaborate to produce high-quality translations. This paper introduces Synslator, a user-friendly computer-aided translation (CAT) tool that not only supports IMT, but is adept at online learning with real-time translation memories. To accommodate various deployment environments for CAT services, Synslator integrates two different neural translation models to handle translation memories for online learning. Additionally, the system employs a language model to enhance the fluency of translations in an interactive mode. In evaluation, we have confirmed the effectiveness of online learning through the translation models, and have observed a 13% increase in post-editing efficiency with the interactive functionalities of Synslator. A tutorial video is available at:https://youtu.be/K0vRsb2lTt8.
@article{arxiv.2310.05025,
title = {Synslator: An Interactive Machine Translation Tool with Online Learning},
author = {Jiayi Wang and Ke Wang and Fengming Zhou and Chengyu Wang and Zhiyong Fu and Zeyu Feng and Yu Zhao and Yuqi Zhang},
journal= {arXiv preprint arXiv:2310.05025},
year = {2023}
}