Publication
ICME 2009
Conference paper

Healthcare audio event classification using hidden Markov models and hierarchical hidden Markov models

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Abstract

Audio is a useful modality complement to video for healthcare monitoring. In this paper, we investigate the use of Hierarchical Hidden Markov Models (HHMMs) for healthcare audio event classification. We show that HHMM can handle audio events with recursive patterns to improve the classification performance. We also propose a model fusion method to cover large variations often existing in healthcare audio events. Experimental results from classifying key eldercare audio events show the effectiveness of the model fusion method for healthcare audio event classification. ©2009 IEEE.

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Publication

ICME 2009

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