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The Spot the Difference corpus: A multi-modal corpus of spontaneous task oriented spoken interactions

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4 Scopus citations

Abstract

This paper describes the Spot the Difference Corpus which contains 54 interactions between pairs of subjects interacting to find differences in two very similar scenes. The setup used, the participants' metadata and details about collection are described. We are releasing this corpus of task-oriented spontaneous dialogues. This release includes rich transcriptions, annotations, audio and video. We believe that this dataset constitutes a valuable resource to study several dimensions of human communication that go from turn-taking to the study of referring expressions. In our preliminary analyses we have looked at task success (how many differences were found out of the total number of differences) and how it evolves over time. In addition we have looked at scene complexity provided by the RGB components' entropy and how it could relate to speech overlaps, interruptions and the expression of uncertainty. We found there is a tendency that more complex scenes have more competitive interruptions.

Original languageEnglish
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsNicoletta Calzolari, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Takenobu Tokunaga
PublisherEuropean Language Resources Association (ELRA)
Pages1939-1945
Number of pages7
ISBN (Electronic)9791095546009
StatePublished - 2018
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: May 7 2018May 12 2018

Publication series

NameLREC 2018 - 11th International Conference on Language Resources and Evaluation

Conference

Conference11th International Conference on Language Resources and Evaluation, LREC 2018
Country/TerritoryJapan
CityMiyazaki
Period05/7/1805/12/18

Keywords

  • Dialogues
  • Multi-modal
  • Spontaneous

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