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A Statistical Model for Unsupervised and Semi-supervised Transliteration Mining

机译:无监督和半监督音译挖掘的统计模型

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摘要

We propose a novel model to automatically extract transliteration pairs from parallel corpora. Our model is efficient, language pair independent and mines transliteration pairs in a consistent fashion in both unsupervised and semi-supervised settings. We model transliteration mining as an interpolation of transliteration and non-transliteration sub-models. We evaluate on NEWS 2010 shared task data and on parallel corpora with competitive results.
机译:我们提出了一种新颖的模型来自动从平行语料库中提取音译对。我们的模型是有效的,独立于语言对,并且在非监督和半监督环境下以一致的方式挖掘音译对。我们将音译挖掘建模为音译和非音译子模型的插值。我们对NEWS 2010共享任务数据和具有竞争性结果的并行语料库进行评估。

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