JH-Ranker: Enhancing Keigo Recognition in Japanese Sentences through Multi-Task Learning-Reference-Cited by-同舟云学术

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JH-Ranker: Enhancing Keigo Recognition in Japanese Sentences through Multi-Task Learning

Published:2024-06-30 Issue: Volume:1 Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Guo Shih-Wei¹,Wen Ya-Chun²,Yu Jui-Ling³,Fan Yao-Chung¹

Affiliation:

1. National Chung Hsing University,Department of Computer Science and Engineering,Taichang,Taiwan

2. Providence University,Department of Japanese Language and Literature,Taichang,Taiwan

3. Providence University,Department of Data Science and Big Data Analytics,Taichang,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10651022.pdf?arnumber=10651022

Reference18 articles.

1. Rethinking context: An introduction;Alessandro,1992

2. Construction and validation of a japanese honorific corpus based on systemic functional linguistics;Liu

3. A deep learning approach for polite dialogue response generation. in proceedings of the international conference on systems;Resmi

4. Polite Dialogue Generation Without Parallel Data

5. Nihongoban cola no kouchiku (constructing japanese cola dataset) (in japanese);Someya

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