# EmoUS: Simulating User Emotions in Task-Oriented Dialogues

arXiv: https://arxiv.org/abs/2306.01579 · HTML: https://mlsanity.com/paper/2306.01579/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 42 references that are in the map.
- First posted on arXiv 2 Jun 2023.

## Builds on (most cited first, 21 of 21)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling](https://mlsanity.com/paper/1810.00278/) (2018)
- [Texygen: A Benchmarking Platform for Text Generation Models](https://mlsanity.com/paper/1802.01886/) (2018)
- [Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances](https://mlsanity.com/paper/1905.02947/) (2019)
- [Affect-Driven Dialog Generation](https://mlsanity.com/paper/1904.02793/) (2019)
- [Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue Systems](https://mlsanity.com/paper/2105.03748/) (2021)
- [Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systems](https://mlsanity.com/paper/1805.06966/) (2018)
- [A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems](https://mlsanity.com/paper/1607.00070/) (2016)
- [User Modeling for Task Oriented Dialogues](https://mlsanity.com/paper/1811.04369/) (2018)
- [Transferable Dialogue Systems and User Simulators](https://mlsanity.com/paper/2107.11904/) (2021)
- [Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systems](https://mlsanity.com/paper/2106.08838/) (2021)
- [GenTUS: Simulating User Behaviour and Language in Task-oriented Dialogues with Generative Transformers](https://mlsanity.com/paper/2208.10817/) (2022)
- [ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data Format](https://mlsanity.com/paper/2211.17148/) (2022)
- [EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems](https://mlsanity.com/paper/2109.04919/) (2021)
- [User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systems](https://mlsanity.com/paper/2202.02912/) (2022)
- [Multi-domain Conversation Quality Evaluation via User Satisfaction Estimation](https://mlsanity.com/paper/1911.08567/) (2019)
- [High-Quality Diversification for Task-Oriented Dialogue Systems](https://mlsanity.com/paper/2106.00891/) (2021)

## Built on by (most cited first, 9 of 9)

- [Reliable LLM-based User Simulator for Task-Oriented Dialogue Systems](https://mlsanity.com/paper/2402.13374/) (2024)
- [Simulating Before Planning: Constructing Intrinsic User World Model for User-Tailored Dialogue Policy Planning](https://mlsanity.com/paper/2504.13643/) (2025)
- [Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation](https://mlsanity.com/paper/2408.02417/) (2024)
- [KAUCUS: Knowledge Augmented User Simulators for Training Language Model Assistants](https://mlsanity.com/paper/2401.16454/) (2024)
- [A Unified Approach to Emotion Detection and Task-Oriented Dialogue Modeling](https://mlsanity.com/paper/2401.13789/) (2024)
- [PicPersona-TOD : A Dataset for Personalizing Utterance Style in Task-Oriented Dialogue with Image Persona](https://mlsanity.com/paper/2504.17390/) (2025)
- [All Learning Has an Emotional Basis, So Does Task-Oriented Dialogue](https://mlsanity.com/paper/2507.01594/) (2025)
- [Hear2Act: Benchmarking When Prosody Should Change What an Assistant Does](https://mlsanity.com/paper/2608.19515/) (2026)
- [PersonaDrift: A Benchmark for Temporal Anomaly Detection in Language-Based Dementia Monitoring](https://mlsanity.com/paper/2511.16445/) (2025)

## Abstract (arXiv)

Existing user simulators (USs) for task-oriented dialogue systems only model user behaviour on semantic and natural language levels without considering the user persona and emotions. Optimising dialogue systems with generic user policies, which cannot model diverse user behaviour driven by different emotional states, may result in a high drop-off rate when deployed in the real world. Thus, we present EmoUS, a user simulator that learns to simulate user emotions alongside user behaviour. EmoUS generates user emotions, semantic actions, and natural language responses based on the user goal, the dialogue history, and the user persona. By analysing what kind of system behaviour elicits what kind of user emotions, we show that EmoUS can be used as a probe to evaluate a variety of dialogue systems and in particular their effect on the user's emotional state. Developing such methods is important in the age of large language model chat-bots and rising ethical concerns.