Synslator: An Interactive Machine Translation Tool with Online Learning

• URL: http://arxiv.org/abs/2310.05025v1
• Date: Sun, 8 Oct 2023 06:05:55 GMT
• Title: Synslator: An Interactive Machine Translation Tool with Online Learning
• Authors: Jiayi Wang, Ke Wang, Fengming Zhou, Chengyu Wang, Zhiyong Fu, Zeyu Feng, Yu Zhao, Yuqi Zhang
• Abstract summary: Interactive machine translation (IMT) has emerged as a progression of the computer-aided translation paradigm. 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.
• Score: 19.6690111454278
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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