A dyadic conversation dataset on moral emotions

Louise Heron; Jaebok Kim; Minha Lee; Kevin El Haddad; Stephane Dupont; Thierry Dutoit; Khiet Truong

doi:10.1109/FG.2018.00108

A dyadic conversation dataset on moral emotions

Louise Heron, Jaebok Kim, Minha Lee, Kevin El Haddad, Stephane Dupont, Thierry Dutoit, Khiet Truong

Department of Psychology

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

9 Citations (SciVal)

Abstract

In this paper, we present a dyadic conversation dataset involving topics related to moral emotions which are ethically relevant. To the best of our knowledge, it is the first dataset where the main focus is moral emotions. This dataset also focuses on speaker-listener reactions during a dyadic conversation. Although some of the currently available datasets contain dyadic conversations, they were not conceived with the idea of focusing on the speaker-listener setup. Thus making it difficult to use them to study reactions related to speakers and listeners. Some preliminary analyses of the data are presented as well as our thoughts on future work related to this dataset.

Original language	English
Title of host publication	Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
Publisher	IEEE
Pages	687-691
Number of pages	5
ISBN (Electronic)	9781538623350
DOIs	https://doi.org/10.1109/FG.2018.00108
Publication status	Published - 5 Jun 2018
Event	13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018 - Xi'an, China Duration: 15 May 2018 → 19 May 2018

Conference

Conference	13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
Country/Territory	China
City	Xi'an
Period	15/05/18 → 19/05/18

Keywords

Affective computing
Dataset
Dyadic interaction
Moral emotions
Multimodal data
Non-verbal expressions

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Control and Optimization

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10.1109/FG.2018.00108

Cite this

Heron, L, Kim, J, Lee, M, El Haddad, K, Dupont, S, Dutoit, T & Truong, K 2018, A dyadic conversation dataset on moral emotions. in Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018. IEEE, pp. 687-691, 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018, Xi'an, China, 15/05/18. https://doi.org/10.1109/FG.2018.00108

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title = "A dyadic conversation dataset on moral emotions",

abstract = "In this paper, we present a dyadic conversation dataset involving topics related to moral emotions which are ethically relevant. To the best of our knowledge, it is the first dataset where the main focus is moral emotions. This dataset also focuses on speaker-listener reactions during a dyadic conversation. Although some of the currently available datasets contain dyadic conversations, they were not conceived with the idea of focusing on the speaker-listener setup. Thus making it difficult to use them to study reactions related to speakers and listeners. Some preliminary analyses of the data are presented as well as our thoughts on future work related to this dataset.",

keywords = "Affective computing, Dataset, Dyadic interaction, Moral emotions, Multimodal data, Non-verbal expressions",

author = "Louise Heron and Jaebok Kim and Minha Lee and {El Haddad}, Kevin and Stephane Dupont and Thierry Dutoit and Khiet Truong",

year = "2018",

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doi = "10.1109/FG.2018.00108",

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note = "13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018 ; Conference date: 15-05-2018 Through 19-05-2018",

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AU - Kim, Jaebok

AU - Lee, Minha

AU - El Haddad, Kevin

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AU - Dutoit, Thierry

AU - Truong, Khiet

PY - 2018/6/5

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N2 - In this paper, we present a dyadic conversation dataset involving topics related to moral emotions which are ethically relevant. To the best of our knowledge, it is the first dataset where the main focus is moral emotions. This dataset also focuses on speaker-listener reactions during a dyadic conversation. Although some of the currently available datasets contain dyadic conversations, they were not conceived with the idea of focusing on the speaker-listener setup. Thus making it difficult to use them to study reactions related to speakers and listeners. Some preliminary analyses of the data are presented as well as our thoughts on future work related to this dataset.

AB - In this paper, we present a dyadic conversation dataset involving topics related to moral emotions which are ethically relevant. To the best of our knowledge, it is the first dataset where the main focus is moral emotions. This dataset also focuses on speaker-listener reactions during a dyadic conversation. Although some of the currently available datasets contain dyadic conversations, they were not conceived with the idea of focusing on the speaker-listener setup. Thus making it difficult to use them to study reactions related to speakers and listeners. Some preliminary analyses of the data are presented as well as our thoughts on future work related to this dataset.

KW - Affective computing

KW - Dataset

KW - Dyadic interaction

KW - Moral emotions

KW - Multimodal data

KW - Non-verbal expressions

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BT - Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018

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Y2 - 15 May 2018 through 19 May 2018

ER -

A dyadic conversation dataset on moral emotions

Abstract

Conference

Keywords

ASJC Scopus subject areas

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