IMTLab: An Open-Source Platform for Building, Evaluating, and Diagnosing Interactive Machine Translation Systems

• URL: http://arxiv.org/abs/2310.11163v1
• Date: Tue, 17 Oct 2023 11:29:04 GMT
• Title: IMTLab: An Open-Source Platform for Building, Evaluating, and Diagnosing Interactive Machine Translation Systems
• Authors: Xu Huang, Zhirui Zhang, Ruize Gao, Yichao Du, Lemao Liu, Gouping Huang, Shuming Shi, Jiajun Chen, Shujian Huang
• Abstract summary: We present IMTLab, an open-source end-to-end interactive machine translation (IMT) system platform. IMTLab treats the whole interactive translation process as a task-oriented dialogue with a human-in-the-loop setting.
• Score: 94.39110258587887
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present IMTLab, an open-source end-to-end interactive machine translation (IMT) system platform that enables researchers to quickly build IMT systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems. IMTLab treats the whole interactive translation process as a task-oriented dialogue with a human-in-the-loop setting, in which human interventions can be explicitly incorporated to produce high-quality, error-free translations. To this end, a general communication interface is designed to support the flexible IMT architectures and user policies. Based on the proposed design, we construct a simulated and real interactive environment to achieve end-to-end evaluation and leverage the framework to systematically evaluate previous IMT systems. Our simulated and manual experiments show that the prefix-constrained decoding approach still gains the lowest editing cost in the end-to-end evaluation, while BiTIIMT achieves comparable editing cost with a better interactive experience.

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