@inproceedings{vacher-etal-2014-sweet,
title = "The Sweet-Home speech and multimodal corpus for home automation interaction",
author = "Vacher, Michel and
Lecouteux, Benjamin and
Chahuara, Pedro and
Portet, Fran{\c{c}}ois and
Meillon, Brigitte and
Bonnefond, Nicolas",
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/118_Paper.pdf",
pages = "4499--4506",
abstract = "Ambient Assisted Living aims at enhancing the quality of life of older and disabled people at home thanks to Smart Homes and Home Automation. However, many studies do not include tests in real settings, because data collection in this domain is very expensive and challenging and because of the few available data sets. The S WEET-H OME multimodal corpus is a dataset recorded in realistic conditions in D OMUS, a fully equipped Smart Home with microphones and home automation sensors, in which participants performed Activities of Daily living (ADL). This corpus is made of a multimodal subset, a French home automation speech subset recorded in Distant Speech conditions, and two interaction subsets, the first one being recorded by 16 persons without disabilities and the second one by 6 seniors and 5 visually impaired people. This corpus was used in studies related to ADL recognition, context aware interaction and distant speech recognition applied to home automation controled through voice.",
}
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%0 Conference Proceedings
%T The Sweet-Home speech and multimodal corpus for home automation interaction
%A Vacher, Michel
%A Lecouteux, Benjamin
%A Chahuara, Pedro
%A Portet, François
%A Meillon, Brigitte
%A Bonnefond, Nicolas
%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 vacher-etal-2014-sweet
%X Ambient Assisted Living aims at enhancing the quality of life of older and disabled people at home thanks to Smart Homes and Home Automation. However, many studies do not include tests in real settings, because data collection in this domain is very expensive and challenging and because of the few available data sets. The S WEET-H OME multimodal corpus is a dataset recorded in realistic conditions in D OMUS, a fully equipped Smart Home with microphones and home automation sensors, in which participants performed Activities of Daily living (ADL). This corpus is made of a multimodal subset, a French home automation speech subset recorded in Distant Speech conditions, and two interaction subsets, the first one being recorded by 16 persons without disabilities and the second one by 6 seniors and 5 visually impaired people. This corpus was used in studies related to ADL recognition, context aware interaction and distant speech recognition applied to home automation controled through voice.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/118_Paper.pdf
%P 4499-4506
Markdown (Informal)
[The Sweet-Home speech and multimodal corpus for home automation interaction](http://www.lrec-conf.org/proceedings/lrec2014/pdf/118_Paper.pdf) (Vacher et al., LREC 2014)
ACL
- Michel Vacher, Benjamin Lecouteux, Pedro Chahuara, François Portet, Brigitte Meillon, and Nicolas Bonnefond. 2014. The Sweet-Home speech and multimodal corpus for home automation interaction. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4499–4506, Reykjavik, Iceland. European Language Resources Association (ELRA).