mlsanityData to 7 Oct 2026

Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation

arXiv 2408.02417 ↗First posted 5 Aug 2024cs.CLcited by 5

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Abstract (arXiv)

Emotions are indispensable in human communication, but are often overlooked in task-oriented dialogue (ToD) modelling, where the task success is the primary focus. While existing works have explored user emotions or similar concepts in some ToD tasks, none has so far included emotion modelling into a fully-fledged ToD system nor conducted interaction with human or simulated users. In this work, we incorporate emotion into the complete ToD processing loop, involving understanding, management, and generation. To this end, we extend the EmoWOZ dataset (Feng et al., 2022) with system affective behaviour labels. Through interactive experimentation involving both simulated and human users, we demonstrate that our proposed framework significantly enhances the user's emotional experience as well as the task success.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 23 of its 45 references that are in the map. First posted on arXiv 5 Aug 2024.

Builds on

23 of 45 references.

References · 23

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  9. 2018Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systemscited by 42
  10. 2022A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-Oriented Dialogue Policy Learningcited by 30
  11. 2021Fusing task-oriented and open-domain dialogues in conversational agentscited by 28
  12. 2021Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systemscited by 23
11 more
  1. 2022GenTUS: Simulating User Behaviour and Language in Task-oriented Dialogues with Generative Transformerscited by 22
  2. 2022ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data Formatcited by 22
  3. 2023UniSA: Unified Generative Framework for Sentiment Analysiscited by 17
  4. 2022Robust Dialogue State Tracking with Weak Supervision and Sparse Datacited by 15
  5. 2022Dynamic Dialogue Policy for Continual Reinforcement Learningcited by 12
  6. 2023EmoUS: Simulating User Emotions in Task-Oriented Dialoguescited by 9
  7. 2021Uncertainty Measures in Neural Belief Tracking and the Effects on Dialogue Policy Performancecited by 8
  8. 2022DialCrowd 2.0: A Quality-Focused Dialog System Crowdsourcing Toolkitcited by 6
  9. 2023Dialogue Quality and Emotion Annotations for Customer Support Conversationscited by 4
  10. 2022Dialogue Evaluation with Offline Reinforcement Learningcited by 3
  11. 2024A Unified Approach to Emotion Detection and Task-Oriented Dialogue Modelingcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.