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Multi-Task Learning for Chinese Word Usage Errors Detection

机译:汉语单词使用错误检测的多任务学习

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Chinese word usage errors often occur in non-native Chinese learners' writing. It is very helpful for non-native Chinese learners to detect them automatically when learning writing. In this paper, we propose a novel approach, which takes advantages of different auxiliary tasks, such as POS-tagging prediction and word log frequency prediction, to help the task of Chinese word usage error detection. With the help of these auxiliary tasks, we achieve the state-of-the-art results on the performances on the HSK corpus data, without any other extra data.
机译:汉语单词使用错误通常发生在非原生学习者的写作中。对于非原生学习者来说,非常有助于在学习写作时自动检测它们。在本文中,我们提出了一种新颖的方法,它采用不同的辅助任务,例如POS标记预测和字日志频率预测,以帮助汉字使用错误检测的任务。在这些辅助任务的帮助下,我们实现了最先进的结果对HSK语料库数据的表现,而无需任何其他额外数据。

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