A Spoken Dialogue System for the EMPATHIC Virtual Coach

Torres, M. Inés; Olaso, Javier Mikel; Glackin, N.; Justo, Raquel; Chollet, Gérard

doi:10.1007/978-981-13-9443-0_22

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…Besides, it is also a promising research direction to involve empathy in various dialogue systems to increase the user experience. For instance, audio-based dialogue systems consider voice tone, intonation, and content of speakers to generate empathetic responses [1,18]. Fung et al investigated empathetic dialogue for booking systems with a latent variable to store the dialog state [19].…”

Section: Empathetic Response Generationmentioning

confidence: 99%

Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality

Wang,

LI,

Lin

et al. 2021

Preprint

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Empathetic response generation aims to comprehend the user emotion and then respond to it appropriately. Most existing works merely focus on what the emotion is and ignore how the emotion is evoked, thus weakening the capacity of the model to understand the emotional experience of the user for generating empathetic responses. To tackle this problem, we consider the emotional causality, namely, what feelings the user expresses (i.e., emotion) and why the user has such feelings (i.e., cause). Then, we propose a novel graph-based model with multi-hop reasoning to model the emotional causality of the empathetic conversation. Finally, we demonstrate the effectiveness of our model on EMPATHET-ICDIALOGUES in comparison with several competitive models.

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Section: Empathetic Response Generationmentioning

confidence: 99%

Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality

Wang,

LI,

Lin

et al. 2021

Preprint

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“…It maintains the state and manages the flow of the conversation by determining the action that the system has to perform at each agent turn. For the EMPATHIC project [9,12], we used an agenda-based management structure based on the RavenClaw [13] dialogue management framework that separates the domain-dependent and the domain-independent components of the conversation, unlike previous plan-based dialogue managers. The domain-specific aspects are defined by a dialogue task specification defined by a tree of dialogue agents.…”

Section: Grow Model Implemented Through the Dialogue Managermentioning

confidence: 99%

A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly

Montenegro¹,

Zorrilla

Olaso

et al. 2019

MTI

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This paper presents a dialogue act taxonomy designed for the developmentof a conversational agent for elderly. The main goal of this conversational agent is to improvelife quality of the user by means of coaching sessions in different topics. In contrast to otherapproaches such as task-oriented dialogue systems and chit-chat implementations, the agent shoulddisplay a pro-active attitude, driving the conversation to reach a number of diverse coachinggoals. Therefore, the main characteristic of the introduced dialogue act taxonomy is its capacityfor supporting a communication based on the GROW model for coaching. In addition, the taxonomyhas a hierarchical structure between the tags and it is multimodal. We use the taxonomy toannotate a Spanish dialogue corpus collected from a group of elder people. We also present apreliminary examination of the annotated corpus and discuss on the multiple possibilities it presentsfor further research.

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“…In this work we deal with a dialogue system developed within the EMPATHIC project [25,26,13] framework. The goal of this project is to design and validate new interaction paradigms for personalized Virtual Coaches to promote healthy and independent aging.…”

Section: Introductionmentioning

confidence: 99%

A Spanish Corpus for Talking to the Elderly

Justo

Letaifa

Olaso

et al. 2020

Lecture Notes in Electrical Engineering

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In this work, a Spanish corpus that was developed, within the EMPATHIC project 1 framework, is presented. It was designed for building a dialogue system capable of talking to elderly people and promoting healthy habits, through a coaching model. The corpus, that comprises audio, video an text channels, was acquired by using a Wizard of Oz strategy. It was annotated in terms of different labels according to the different models that are needed in a dialogue system, including an emotion based annotation that will be used to generate empathetic system reactions. The annotation at different levels along with the employed procedure are described and analysed.1 http://www.empathic-project.eu/

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A Spoken Dialogue System for the EMPATHIC Virtual Coach

Cited by 7 publications

References 15 publications

Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality

Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality

A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly

A Spanish Corpus for Talking to the Elderly

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