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Two-step detection of water sound events for the diagnostic and monitoring of dementia

Abstract : A significant aging of world population is foreseen for the next decades. Thus, developing technologies to empower the independency and assist the elderly are becoming of great interest. In this framework, the IMMED project investigates tele-monitoring technologies to support doctors in the diagnostic and follow-up of dementia illnesses such as Alzheimer. Specifically, water sounds are very useful to track and identify abnormal behaviors form everyday activities (e.g. hygiene, household, cooking, etc.). In this work, we propose a double-stage system to detect this type of sound events. In the first stage, the audio stream is segmented with a simple but effective algorithm based on the Spectral Cover feature. The second stage improves the system precision by classifing the segmented streams into water/non-water sound events using Gammatone Cepstral Coefficients and Support Vector Machines. Experimental results reveal the potential of the combined system, yielding a F-measure higher than 80%.
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Submitted on : Monday, May 4, 2015 - 10:53:36 AM
Last modification on : Friday, August 27, 2021 - 11:26:03 AM
Long-term archiving on: : Monday, September 14, 2015 - 6:07:05 PM


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  • HAL Id : hal-01148156, version 1
  • OATAO : 12441


Patrice Guyot, Julien Pinquier, Xavier Valero Gonzalez, Francesc Alias. Two-step detection of water sound events for the diagnostic and monitoring of dementia. IEEE International Conference on Multimedia & Expo - ICME, Jul 2013, San Jose, United States. pp. 1-6. ⟨hal-01148156⟩



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