The Tutorbot Corpus — A Corpus for Studying Tutoring Behaviour in Multiparty Face-to-Face Spoken Dialogue

Maria Koutsombogera, Samer Al Moubayed, Bajibabu Bollepalli, Ahmed Hussen Abdelaziz, Martin Johansson, José David Aguas Lopes, Jekaterina Novikova, Catharine Oertel, Kalin Stefanov, Gül Varol

[How to correct problems with metadata yourself]


Abstract
This paper describes a novel experimental setup exploiting state-of-the-art capture equipment to collect a multimodally rich game-solving collaborative multiparty dialogue corpus. The corpus is targeted and designed towards the development of a dialogue system platform to explore verbal and nonverbal tutoring strategies in multiparty spoken interactions. The dialogue task is centered on two participants involved in a dialogue aiming to solve a card-ordering game. The participants were paired into teams based on their degree of extraversion as resulted from a personality test. With the participants sits a tutor that helps them perform the task, organizes and balances their interaction and whose behavior was assessed by the participants after each interaction. Different multimodal signals captured and auto-synchronized by different audio-visual capture technologies, together with manual annotations of the tutor’s behavior constitute the Tutorbot corpus. This corpus is exploited to build a situated model of the interaction based on the participants’ temporally-changing state of attention, their conversational engagement and verbal dominance, and their correlation with the verbal and visual feedback and conversation regulatory actions generated by the tutor.
Anthology ID:
L14-1641
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
4196–4201
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/832_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Maria Koutsombogera, Samer Al Moubayed, Bajibabu Bollepalli, Ahmed Hussen Abdelaziz, Martin Johansson, José David Aguas Lopes, Jekaterina Novikova, Catharine Oertel, Kalin Stefanov, and Gül Varol. 2014. The Tutorbot Corpus — A Corpus for Studying Tutoring Behaviour in Multiparty Face-to-Face Spoken Dialogue. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4196–4201, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
The Tutorbot Corpus — A Corpus for Studying Tutoring Behaviour in Multiparty Face-to-Face Spoken Dialogue (Koutsombogera et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/832_Paper.pdf