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Who will get the grant?: A multimodal corpus for the analysis of conversational behaviours in group interviews
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0002-8273-0132
Show others and affiliations
2014 (English)In: UM3I 2014 - Proceedings of the 2014 ACM Workshop on Understanding and Modeling Multiparty, Multimodal Interactions, Co-located with ICMI 2014, Association for Computing Machinery (ACM), 2014, 27-32 p.Conference paper, Published paper (Refereed)
Abstract [en]

In the last couple of years more and more multimodal corpora have been created. Recently many of these corpora have also included RGB-D sensors' data. However, there is to our knowledge no publicly available corpus, which combines accurate gaze-tracking, and high- quality audio recording for group discussions of varying dynamics. With a corpus that would fulfill these needs, it would be possible to investigate higher level constructs such as group involvement, individual engagement or rapport, which all require multimodal feature extraction. In the following paper we describe the design and recording of such a corpus and we provide some illustrative examples of how such a corpus might be exploited in the study of group dynamics.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2014. 27-32 p.
Keyword [en]
Corpus collection, Eye-gaze, Group dynamics, Involvement
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-158171DOI: 10.1145/2666242.2666251Scopus ID: 2-s2.0-84919344128ISBN: 978-145030652-2 (print)OAI: oai:DiVA.org:kth-158171DiVA: diva2:774972
Conference
ICMI 2014 Workshop on Understanding and Modeling Multiparty, Multimodal Interactions, UM3I 2014, Istanbul, Turkey, 16 November 2014
Note

QC 20150203

Available from: 2014-12-30 Created: 2014-12-30 Last updated: 2016-12-13Bibliographically approved
In thesis
1. Modelling Engagement in Multi-Party Conversations: Data-Driven Approaches to Understanding Human-Human Communication Patterns for Use in Human-Robot Interactions
Open this publication in new window or tab >>Modelling Engagement in Multi-Party Conversations: Data-Driven Approaches to Understanding Human-Human Communication Patterns for Use in Human-Robot Interactions
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of this thesis is to study human-human interaction in order to provide virtual agents and robots with the capability to engage into multi-party-conversations in a human-like-manner. The focus lies with the modelling of conversational dynamics and the appropriate realization of multi-modal feedback behaviour. For such an undertaking, it is important to understand how human-human communication unfolds in varying contexts and constellations over time. To this end, multi-modal human-human corpora are designed as well as annotation schemes to capture conversational dynamics are developed. Multi-modal analysis is carried out and models are built. Emphasis is put on not modelling speaker behaviour in general and on modelling listener behaviour in particular.

In this thesis, a bridge is built between multi-modal modelling of conversational dynamics on the one hand multi-modal generation of listener behaviour in virtual agents and robots on the other hand. In order to build this bridge, a unit-selection multi-modal synthesis is carried out as well as a statistical speech synthesis of feedback. The effect of a variation in prosody of feedback token on the perception of third-party observers is evaluated. Finally, the effect of a controlled variation of eye-gaze is evaluated, as is the perception of user feedback in human-robot interaction.​

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2016. 87 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2017:05
National Category
Engineering and Technology
Research subject
Human-computer Interaction
Identifiers
urn:nbn:se:kth:diva-198175 (URN)978-91-7729-237-1 (ISBN)
Public defence
2017-01-20, F3, Lindstedtsvägen 26, Kungl Tekniska högskolan, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20161214

Available from: 2016-12-14 Created: 2016-12-13 Last updated: 2016-12-14Bibliographically approved

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Gustafson, Joakim

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