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

TL;DR

This paper introduces a comprehensive emotion-aware task-oriented dialogue system that improves user experience and task success by integrating emotion understanding, management, and generation, validated through experiments with human and simulated users.

Contribution

It is the first to fully incorporate emotion modeling into a complete task-oriented dialogue system and evaluate its impact through interactive experiments.

Findings

Enhanced user emotional experience

Improved task success rates

Effective emotion integration in dialogue systems

Abstract

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.