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

Fuente: arXiv
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Autores principales: Feng, Shutong, Lin, Hsien-chin, Geishauser, Christian, Lubis, Nurul, van Niekerk, Carel, Heck, Michael, Ruppik, Benjamin, Vukovic, Renato, Gašić, Milica
Formato: Preprint
Publicado: 2024
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author Feng, Shutong
Lin, Hsien-chin
Geishauser, Christian
Lubis, Nurul
van Niekerk, Carel
Heck, Michael
Ruppik, Benjamin
Vukovic, Renato
Gašić, Milica
author_facet Feng, Shutong
Lin, Hsien-chin
Geishauser, Christian
Lubis, Nurul
van Niekerk, Carel
Heck, Michael
Ruppik, Benjamin
Vukovic, Renato
Gašić, Milica
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2408_02417
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation
Feng, Shutong
Lin, Hsien-chin
Geishauser, Christian
Lubis, Nurul
van Niekerk, Carel
Heck, Michael
Ruppik, Benjamin
Vukovic, Renato
Gašić, Milica
Computation and Language
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.
title Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation
topic Computation and Language
url https://arxiv.org/abs/2408.02417