@inproceedings{hennig-etal-2014-ans,
title = "The {D}-{ANS} corpus: the {D}ublin-Autonomous Nervous System corpus of biosignal and multimodal recordings of conversational speech",
author = "Hennig, Shannon and
Chellali, Ryad and
Campbell, Nick",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/374_Paper.pdf",
pages = "3438--3443",
abstract = "Biosignals, such as electrodermal activity (EDA) and heart rate, are increasingly being considered as potential data sources to provide information about the temporal fluctuations in affective experience during human interaction. This paper describes an English-speaking, multiple session corpus of small groups of people engaged in informal, unscripted conversation while wearing wireless, wrist-based EDA sensors. Additionally, one participant per recording session wore a heart rate monitor. This corpus was collected in order to observe potential interactions between various social and communicative phenomena and the temporal dynamics of the recorded biosignals. Here we describe the communicative context, technical set-up, synchronization process, and challenges in collecting and utilizing such data. We describe the segmentation and annotations to date, including laughter annotations, and how the research community can access and collaborate on this corpus now and in the future. We believe this corpus is particularly relevant to researchers interested in unscripted social conversation as well as to researchers with a specific interest in observing the dynamics of biosignals during informal social conversation rich with examples of laughter, conversational turn-taking, and non-task-based interaction.",
}
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%0 Conference Proceedings
%T The D-ANS corpus: the Dublin-Autonomous Nervous System corpus of biosignal and multimodal recordings of conversational speech
%A Hennig, Shannon
%A Chellali, Ryad
%A Campbell, Nick
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F hennig-etal-2014-ans
%X Biosignals, such as electrodermal activity (EDA) and heart rate, are increasingly being considered as potential data sources to provide information about the temporal fluctuations in affective experience during human interaction. This paper describes an English-speaking, multiple session corpus of small groups of people engaged in informal, unscripted conversation while wearing wireless, wrist-based EDA sensors. Additionally, one participant per recording session wore a heart rate monitor. This corpus was collected in order to observe potential interactions between various social and communicative phenomena and the temporal dynamics of the recorded biosignals. Here we describe the communicative context, technical set-up, synchronization process, and challenges in collecting and utilizing such data. We describe the segmentation and annotations to date, including laughter annotations, and how the research community can access and collaborate on this corpus now and in the future. We believe this corpus is particularly relevant to researchers interested in unscripted social conversation as well as to researchers with a specific interest in observing the dynamics of biosignals during informal social conversation rich with examples of laughter, conversational turn-taking, and non-task-based interaction.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/374_Paper.pdf
%P 3438-3443
Markdown (Informal)
[The D-ANS corpus: the Dublin-Autonomous Nervous System corpus of biosignal and multimodal recordings of conversational speech](http://www.lrec-conf.org/proceedings/lrec2014/pdf/374_Paper.pdf) (Hennig et al., LREC 2014)
ACL