利用 OPUS-MT 实现神经机器翻译的民主化

IF 1.7 3区计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Language Resources and Evaluation Pub Date : 2023-12-13 DOI:10.1007/s10579-023-09704-w

Jörg Tiedemann, Mikko Aulamo, Daria Bakshandaeva, Michele Boggia, Stig-Arne Grönroos, Tommi Nieminen, Alessandro Raganato, Yves Scherrer, Raúl Vázquez, Sami Virpioja

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引用次数: 0

摘要

本文介绍了OPUS生态系统，重点关注开放式机器翻译模型和工具的开发，以及它们与最终用户应用程序、开发平台和专业工作流程的集成。我们讨论了增加语言覆盖率和翻译质量的持续任务，并描述了在开发模块化翻译模型和速度优化的紧凑型解决方案方面的工作，用于在常规桌面和小型设备上进行实时翻译。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Democratizing neural machine translation with OPUS-MT

查看原文本刊更多论文

Democratizing neural machine translation with OPUS-MT

This paper presents the OPUS ecosystem with a focus on the development of open machine translation models and tools, and their integration into end-user applications, development platforms and professional workflows. We discuss our ongoing mission of increasing language coverage and translation quality, and also describe work on the development of modular translation models and speed-optimized compact solutions for real-time translation on regular desktops and small devices.

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来源期刊

Language Resources and Evaluation 工程技术-计算机：跨学科应用

CiteScore

6.50

自引率

3.70%

发文量

审稿时长

>12 weeks

期刊介绍： Language Resources and Evaluation is the first publication devoted to the acquisition, creation, annotation, and use of language resources, together with methods for evaluation of resources, technologies, and applications. Language resources include language data and descriptions in machine readable form used to assist and augment language processing applications, such as written or spoken corpora and lexica, multimodal resources, grammars, terminology or domain specific databases and dictionaries, ontologies, multimedia databases, etc., as well as basic software tools for their acquisition, preparation, annotation, management, customization, and use. Evaluation of language resources concerns assessing the state-of-the-art for a given technology, comparing different approaches to a given problem, assessing the availability of resources and technologies for a given application, benchmarking, and assessing system usability and user satisfaction.