Vocal-diary : A voice command based ground truth collection system for activity recognition

Proceedings - Wireless Health 2014, WH 2014

Volumn , Issue , 2014, Pages

  Hoque, Enamul ^a   Dickerson, Robert F ^a   Stankovic, John A ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

Activity recognition; Deployment; Ground truth

Indexed keywords

SEARCH ENGINES;

ACTIVITY RECOGNITION; COLLECTION SYSTEMS; DEPLOYMENT; ENVIRONMENTAL NOISE; GROUND TRUTH; SPEAKER RECOGNITION; VOICE COMMAND; VOICE COMMAND RECOGNITION;

SPEECH RECOGNITION;

EID: 84919372211     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2668883.2669587     Document Type: Conference Paper

References (17)

1. Microsoft speech api (sapi). http://msdn.microsoft.com/en-us/library/ms723627(v=vs.85).aspx 2014.
2. M. Buettner, R. Prasad, M. Philipose, and D. Wetherall. Recognizing daily activities with rfid-based.
3. D. Cook and M. Schmitter-Edgecombe. Assessing the quality of activities in a smart environment. Methods of Information in Medicine, 48(5), 2009.
4. R. Dickerson, E. Hoque, P. Asare,, S. Nirjon, and J. Stankovic. Resonate: Improving speech classification in home environments using reverberant environment simulation. In IPSN, 2014.
5. T. Gu, S. Chen, X. Tao, and J. Lu. An unsupervised approach to activity recognition and segmentation based on object-use fingerprints. Data Knowl. Eng., 69(6), 2010.
6. M. R. Hodges, N. L. Kirsch, M. W. Newman, and M. E. Pollack. Automatic assessment of cognitive impairment through electronic observation of object usage. In Pervasive, 2010.
7. T. Huynh, M. Fritz, and B. Schiele. Discovery of activity patterns using topic models. In UbiComp, 2008.
8. T. Kasteren, G. Englebienne, and B. J. A. Kröse. Activity recognition using semi-markov models on real world smart home datasets. J. Ambient Intell. Smart Environ., 2(3), 2010.
9. T. Kasteren, A. Noulas, G. Englebienne, and B. Kröse. Accurate activity recognition in a home setting. In UbiComp, 2008.
10. P. Klasnja, B. L. Harrison, L. LeGrand, A. LaMarca, J. Froehlich, and S. E. Hudson. Using wearable sensors and real time inference to understand human recall of routine activities, 2008.
11. B. Logan, J. Healey, M. Philipose, E. M. Tapia, and S. Intille. A long-term evaluation of sensing modalities for activity recognition. In UbiComp, 2007.
12. D. Lymberopoulos, A. Bamis, and A. Savvides. Extracting spatiotemporal human activity patterns in assisted living using a home sensor network. In PETRA, 2008.
13. S. A. Mokhov. Evolution of marf and its nlp framework. In Proceedings of the Third C∗ Conference on Computer Science and Software Engineering, C3S2E '10, 2010.
14. A. Möller, M. Kranz, B. Schmid, L. Roalter, and S. Diewald. Investigating self-reporting behavior in long-term studies. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2013.
15. T. Mori, A. Takada, Y. lwamura, and T. Sato. Automatic human life summarization system in sensory living space. In International Conference on Systems, Man and Cybernetics, 2004.
16. E. M. Tapia, T. Choudhury, and M. Philipose. Building reliable activity models using hierarchical shrinkage and mined ontology. In Pervasive, 2006.
17. J. Wu, A. Osuntogun, T. Choudhury, M. Philipose, and J. M. Rehg. A scalable approach to activity recognition based on object use. In ICCV, 2007.