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Synslator: An Interactive Machine Translation Tool with Online Learning (2310.05025v1)

Published 8 Oct 2023 in cs.CL

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 LLM 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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Authors (8)
  1. Jiayi Wang (74 papers)
  2. Ke Wang (531 papers)
  3. Fengming Zhou (4 papers)
  4. Chengyu Wang (93 papers)
  5. Zhiyong Fu (1 paper)
  6. Zeyu Feng (8 papers)
  7. Yu Zhao (208 papers)
  8. Yuqi Zhang (54 papers)

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