Learning Co-Occurrence of Laughter and Topics in Conversational Interactions

Kristiina Jokinen; Junpei Zhong

doi:10.1109/SMC42975.2020.9283317

Learning Co-Occurrence of Laughter and Topics in Conversational Interactions

Kristiina Jokinen, Junpei Zhong

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

This paper describes experiments to learn laughter co-occurrences with dialogue contributions. The dialogue data belongs to the special type of First Encounter Dialogues where the interlocutors meet each other for the first time and where laughter mainly functions as a sign of politeness or relief of embarrassment. The earlier studies have shown that there is a correlation between the speaker's utterance content (topic) and non-verbal communication (laughter and body movement) while in this paper we seek to learn the correlations via a neural model. The results show that there seems to be a weak correlation in our data.

Original language	English
Title of host publication	2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3845-3851
Number of pages	7
Volume	2020-October
ISBN (Electronic)	9781728185262
DOIs	https://doi.org/10.1109/SMC42975.2020.9283317
Publication status	Published - 14 Dec 2020
Externally published	Yes
Event	2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 - Toronto, Canada Duration: 11 Oct 2020 → 14 Oct 2020

Conference

Conference	2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
Country/Territory	Canada
City	Toronto
Period	11/10/20 → 14/10/20

Keywords

component
formatting
insert
style
styling

ASJC Scopus subject areas

Software
Control and Systems Engineering
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

More information

10.1109/SMC42975.2020.9283317

Cite this

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title = "Learning Co-Occurrence of Laughter and Topics in Conversational Interactions",

abstract = "This paper describes experiments to learn laughter co-occurrences with dialogue contributions. The dialogue data belongs to the special type of First Encounter Dialogues where the interlocutors meet each other for the first time and where laughter mainly functions as a sign of politeness or relief of embarrassment. The earlier studies have shown that there is a correlation between the speaker's utterance content (topic) and non-verbal communication (laughter and body movement) while in this paper we seek to learn the correlations via a neural model. The results show that there seems to be a weak correlation in our data.",

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author = "Kristiina Jokinen and Junpei Zhong",

note = "Funding Information: The research was supported by Japan New Energy and Industrial Technology Development Organization (NEDO). Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 ; Conference date: 11-10-2020 Through 14-10-2020",

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Jokinen, K & Zhong, J 2020, Learning Co-Occurrence of Laughter and Topics in Conversational Interactions. in 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020. vol. 2020-October, 9283317, Institute of Electrical and Electronics Engineers Inc., pp. 3845-3851, 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020, Toronto, Canada, 11/10/20. https://doi.org/10.1109/SMC42975.2020.9283317

Learning Co-Occurrence of Laughter and Topics in Conversational Interactions. / Jokinen, Kristiina; Zhong, Junpei.
2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020. Vol. 2020-October Institute of Electrical and Electronics Engineers Inc., 2020. p. 3845-3851 9283317.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Learning Co-Occurrence of Laughter and Topics in Conversational Interactions

AU - Jokinen, Kristiina

AU - Zhong, Junpei

PY - 2020/12/14

Y1 - 2020/12/14

N2 - This paper describes experiments to learn laughter co-occurrences with dialogue contributions. The dialogue data belongs to the special type of First Encounter Dialogues where the interlocutors meet each other for the first time and where laughter mainly functions as a sign of politeness or relief of embarrassment. The earlier studies have shown that there is a correlation between the speaker's utterance content (topic) and non-verbal communication (laughter and body movement) while in this paper we seek to learn the correlations via a neural model. The results show that there seems to be a weak correlation in our data.

AB - This paper describes experiments to learn laughter co-occurrences with dialogue contributions. The dialogue data belongs to the special type of First Encounter Dialogues where the interlocutors meet each other for the first time and where laughter mainly functions as a sign of politeness or relief of embarrassment. The earlier studies have shown that there is a correlation between the speaker's utterance content (topic) and non-verbal communication (laughter and body movement) while in this paper we seek to learn the correlations via a neural model. The results show that there seems to be a weak correlation in our data.

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KW - formatting

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KW - style

KW - styling

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BT - 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020

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Learning Co-Occurrence of Laughter and Topics in Conversational Interactions

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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