基于迁移学习的小训练数据集意图理解

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI:10.23919/ICMU.2018.8653619

Hideaki Joko, Yusuke Koji, Hayato Uchide, Takahiro Otsuka

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引用次数: 0

摘要

本研究提出了一种基于迁移学习的日英翻译数据意图理解方法。研究发现，在小数据训练情况下，本文方法的性能比基线方法有所提高，当每个意图标签的数据数为1时，意图理解准确率最高提高10.8分。

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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Intention Understanding in Small Training Data Sets by Using Transfer Learning

This research proposes an intention understanding method that uses transfer learning from Japanese-English translation data. It was found that the proposed method improved performance over the baseline method for small training data, with intention understanding accuracy improving by a maximum of 10.8 points when the number of data for each intention label was 1.

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来源期刊

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)

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