Summary of the paper

Title The Sweet-Home Speech and Multimodal Corpus for Home Automation Interaction
Authors Michel Vacher, Benjamin Lecouteux, Pedro Chahuara, François Portet, Brigitte Meillon and Nicolas Bonnefond
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.
Topics Corpus (Creation, Annotation, etc.), Speech Resource/Database
Full paper The Sweet-Home Speech and Multimodal Corpus for Home Automation Interaction
Bibtex @InProceedings{VACHER14.118,
  author = {Michel Vacher and Benjamin Lecouteux and Pedro Chahuara and François Portet and Brigitte Meillon and Nicolas Bonnefond},
  title = {The Sweet-Home Speech and Multimodal Corpus for Home Automation Interaction},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
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