Joint Dual Learning With Mutual Information Maximization for Natural Language Understanding and Generation in Dialogues-Reference-Cited by-同舟云学术

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Joint Dual Learning With Mutual Information Maximization for Natural Language Understanding and Generation in Dialogues

Published:2024 Issue: Volume:32 Page:2445-2452
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Su Shang-Yu¹^ORCID,Chung Yung-Sung²^ORCID,Chen Yun-Nung³^ORCID

Affiliation:

1. Rakuten Institute of Technology, Rakuten, Tokyo, Japan

2. Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA

3. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

Funder

National Science and Technology Council

Young Scholar Fellowship Program

Google

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570655/10304349/10477541.pdf?arnumber=10477541

Reference41 articles.

1. Spoken Language Understanding

2. Multi-domain joint semantic frame parsing using bi-directional RNN-LSTM;Hakkani-Tr,2016

3. Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning

4. Discriminative Deep Dyna-Q: Robust Planning for Dialogue Policy Learning

5. Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems

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