The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Sweet-Home speech and multimodal corpus for home automation interaction
Open accessAbstract
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 SWEET-HOME multimodal corpus is a dataset recorded in realistic conditions in DOMUS, 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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The SWEET-HOME corpus may only be used for system adaptation purposes because no emergency calls were included in it.
“Unfortunately, this corpus may only be used for system adaptation purposes because no emergency call were included in it.”
From Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House (2019) · cites this paper as Vacher et al., 2014
Section 4.4 says the corpus includes distress calls, reporting 348 in clean conditions, 192 with radio noise, and 205 with music. It distinguishes those recordings from the text used for acoustic adaptation, contradicting both the stated reason and the claim that the corpus can only be used for adaptation. (LLM, conf=0.95)
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Portet, F., Vacher, M., Golanski, C., Roux, C., & Meillon, B. (2013) · Personal and Ubiquitous Computing · doi:10.1007/s00779-011-0470-5 · Cited by 421
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Research works printed but not linked: 17
- References P. Chahuara, A. Fleury, F. Portet, and M. Vacher. 2012. Us- ing Markov Logic Network for On-line Activity Recog- nition from Non-Visual Home Automation Sensors. In Ambient Intelligence, volume 7683 of Lecture Notes in Computer Science, pages 177-192. Springer (Heidel- berg).
- P. Chahuara, F. Portet, and M. Vacher. 2013. Making Con- text Aware Decision from Uncertain Information in a Smart Home: A Markov Logic Network Approach. In Ambient Intelligence, volume 8309 of Lecture Notes in Computer Science, pages 78-93. Springer.
- M. Chan, D. Estève, C. Escriba, and E. Campo. 2008. A review of smart homes-present state and fu- ture challenges. Computer Methods and Programs in Biomedicine, 91(1):55-81.
- H. Christensen, J. Barker, N. Ma, and P. Green. 2010. The CHiME corpus: a resource and a challenge for computa- tional hearing in multisource environments. In Proceed- ings of Interspeech 2010, pages 1918-1921.
- M. Cooke, J. Barker, S. Cunningham, and X. Shao. 2006. An audio-visual corpus for speech perception and auto- matic speech recognition. Journal of the Acoustical So- ciety of America, 120:2421-2424.
- Joëlle Coutaz, James L. Crowley, Simon Dobson, and David Garlan. 2005. Context is key. Communications of the ACM, 48(3):49-53.
- A. Fleury, M. Vacher, and N. Noury. 2010. SVM-based multi-modal classification of activities of daily living in health smart homes: Sensors, algorithms and first exper- imental results. IEEE Transactions on Information Tech- nology in Biomedicine, 14(2):274 -283, march.
- A. Fleury, M. Vacher, F. Portet, P. Chahuara, and N. Noury. 2013. A French corpus of audio and multimodal inter- actions in a health smart home. Journal on Multimodal User Interfaces, 7(1):93-109.
- S. Katz and C.A. Akpom. 1976. A measure of primary so- ciobiological functions. International Journal of Health Services, 6(3):493-508.
- B. Lecouteux, M. Vacher, and F. Portet. 2011. Distant speech recognition for home automation: Preliminary experimental results in a smart home. In IEEE SPED 2011, pages 41-50, Brasow, Romania, May 18-21.
- G. Linarès, P. Nocéra, D. Massonié, and D. Matrouf. 2007. The LIA speech recognition system: from 10xRT to 1xRT. In Proc. TSD'07, pages 302-308.
- M. Vacher, A. Fleury, J.-F. Serignat, N. Noury, and H. Glas- son. 2008. Preliminary evaluation of speech/sound recognition for telemedicine application in a real en- vironment. In Proceedings of Interspeech 2008, pages 496-499, Brisbane, Australia, Sep. 22-26.
- M. Vacher, B. Lecouteux, and F. Portet. 2012. Recogni- tion of Voice Commands by Multisource ASR and Noise Cancellation in a Smart Home Environment. In EU- SIPCO, pages 1663-1667, aug.
- M. Vacher, P. Chahuara, B. Lecouteux, D. Istrate, F. Portet, T. Joubert, M. Sehili, B. Meillon, N. Bonnefond, S. Fabre, C. Roux, and S. Caffiau. 2013a. The SWEET- HOME Project: Audio Technology in Smart Homes to improve Well-being and Reliance. In 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'13), pages 7298- 7301, Osaka, Japan.
- M. Vacher, B. Lecouteux, D. Istrate, T. Joubert, F. Portet, M. Sehili, and P. Chahuara. 2013b. Evaluation of a Real- Time Voice Order Recognition System from Multiple Audio Channels in a Home. In Proceedings of Inter- speech 2013, pages 2062-2064.
- M. Vacher, B. Lecouteux, D. Istrate, T. Joubert, F. Portet, M. Sehili, and P. Chahuara. 2013c. Experimental Eval- uation of Speech Recognition Technologies for Voice- based Home Automation Control in a Smart Home. In 4th Workshop on Speech and Language Processing for Assistive Technologies, pages 99-105, Grenoble, France.
- M. Wölfel and J. McDonough. 2009. Distant Speech Recognition. John Wiley and Sons, 573 pages.
Cited by
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Vacher, M., Caffiau, S., Portet, F., Meillon, B., Roux, C., Elias, E., Lecouteux, B., & Chahuara, P. (2015) · ACM Transactions on Accessible Computing · doi:10.1145/2738047 · Cited by 73
Self-citationVacher, M., Aman, F., Rossato, S., Portet, F., & Lecouteux, B. (2019) · ACM Transactions on Accessible Computing · doi:10.1145/3310132 · Cited by 10
Self-citation
Metadata
- Authors
- Vacher, M., Lecouteux, B., Chahuara, P., Portet, F., Meillon, B., & Bonnefond, N.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Venue
- Proceedings of the Language Resources and Evaluation Conference
- Published
- 2014-05
- Pages
- 4499-4506
- ISSN
- 2522-2686
- OpenAlex
- W2250629451
- Cited by
- 51
- References
- 1
- Citations by year
- 2026: 1 · 2023: 3 · 2022: 2 · 2021: 1 · 2020: 8 · 2019: 6 · 2018: 7 · 2017: 2 · 2016: 8 · 2015: 10 · 2014: 3
- FWCI
- 4.06
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Language Resources and Evaluation Conference (LREC) (publishedVersion, cc-by-nc)
- HAL (submittedVersion, other-oa)
- Funders
- Agence Nationale de la Recherche (ANR-09-VERS-011)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- home automation, ambient assisted living, multimodal corpus, speech corpus, activities of daily living, distant speech recognition, voice-controlled home automation, older adults, visually impaired users, context-aware interaction, French speech
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