Report of NEWS 2009 Machine Transliteration Shared Task

Haizhou Li, A. Kumaran, V. Pervouchine, Min Zhang
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引用次数: 93

Abstract

This report documents the details of the Machine Transliteration Shared Task conducted as a part of the Named Entities Workshop (NEWS), an ACL-IJCNLP 2009 workshop. The shared task features machine transliteration of proper names from English to a set of languages. This shared task has witnessed enthusiastic participation of 31 teams from all over the world, with diversity of participation for a given system and wide coverage for a given language pair (more than a dozen participants per language pair). Diverse transliteration methodologies are represented adequately in the shared task for a given language pair, thus underscoring the fact that the workshop may truly indicate the state of the art in machine transliteration in these language pairs. We measure and report 6 performance metrics on the submitted results. We believe that the shared task has successfully achieved the following objectives: (i) bringing together the community of researchers in the area of Machine Transliteration to focus on various research avenues, (ii) Calibrating systems on common corpora, using common metrics, thus creating a reasonable baseline for the state-of-the-art of transliteration systems, and (iii) providing a quantitative basis for meaningful comparison and analysis between various algorithmic approaches used in machine transliteration. We believe that the results of this shared task would uncover a host of interesting research problems, giving impetus to research in this significant research area.
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NEWS 2009机器音译共享任务报告
本报告记录了作为命名实体研讨会(NEWS)的一部分的机器音译共享任务的细节,这是一个ACL-IJCNLP 2009研讨会。共享任务的特点是机器将专有名称从英语音译为一组语言。这个共同的任务见证了来自世界各地的31个团队的热情参与,给定系统的参与多样性和给定语言对的广泛覆盖(每个语言对超过12个参与者)。不同的音译方法在给定语言对的共享任务中得到了充分的体现,从而强调了这样一个事实,即研讨会可能真正表明了这些语言对的机器音译技术的现状。我们测量并报告提交结果的6个性能指标。我们认为,这项共同任务已成功实现以下目标:(i)将机器音译领域的研究人员聚集在一起,专注于各种研究途径;(ii)在通用语料库上校准系统,使用通用指标,从而为最先进的音译系统创建合理的基线;(iii)为机器音译中使用的各种算法方法之间的有意义的比较和分析提供定量基础。我们相信,这项共同任务的结果将揭示一系列有趣的研究问题,推动这一重要研究领域的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Report of NEWS 2016 Machine Transliteration Shared Task Transliteration by Bidirectional Statistical Machine Translation Analysis and Robust Extraction of Changing Named Entities NEWS 2009 Machine Transliteration Shared Task System Description: Transliteration with Letter-to-Phoneme Technology Phonological Context Approximation and Homophone Treatment for NEWS 2009 English-Chinese Transliteration Shared Task
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