Applying Emotional Keyphrase Correlation for Diversity Enhancement in Empathetic Dialogue Response Generation

Jeremy Chang, Chung Hsien Wu

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Developing an empathetic dialogue system has been facing challenges for years. Although most of the responses generated from the existing empathetic dialogue systems are to some extent grammatical and emotional, they are still far from human standards. The system-generated responses are usually uncorrelated to the user's emotional contexts. In this paper, we propose an approach to automatic extraction of the emotional keyphrases from the context, then the emotional keyphrases are fed into the Conditional Transformer language model as the conditional information. We also design a loss function called Keyphrase Correlation (KPC) to guide the model to generate responses with relevant emotional keyphrases. As a result, the diversity of the generated responses is highly enhanced. The experimental results also verified the effectiveness in terms of empathy capability and emotional correlation in the user-system conversation.

原文English
主出版物標題2022 International Conference on Asian Language Processing, IALP 2022
編輯Rong Tong, Yanfeng Lu, Minghui Dong, Wengao Gong, Haizhou Li
發行者Institute of Electrical and Electronics Engineers Inc.
頁面286-291
頁數6
ISBN(電子)9781665476744
DOIs
出版狀態Published - 2022
事件2022 International Conference on Asian Language Processing, IALP 2022 - Singapore, Singapore
持續時間: 2022 10月 272022 10月 28

出版系列

名字2022 International Conference on Asian Language Processing, IALP 2022

Conference

Conference2022 International Conference on Asian Language Processing, IALP 2022
國家/地區Singapore
城市Singapore
期間22-10-2722-10-28

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用
  • 語言和語言學

指紋

深入研究「Applying Emotional Keyphrase Correlation for Diversity Enhancement in Empathetic Dialogue Response Generation」主題。共同形成了獨特的指紋。

引用此