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Computer Science > Computation and Language

arXiv:2310.05025 (cs)
[Submitted on 8 Oct 2023]

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
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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:this https URL.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2310.05025 [cs.CL]
  (or arXiv:2310.05025v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2310.05025

Submission history

From: Jiayi Wang [view email]
[v1] Sun, 8 Oct 2023 06:05:55 UTC (1,140 KB)
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