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Water sound recognition based on physical models

Guyot, Patrice and Pinquier, Julien and André-Obrecht, Régine Water sound recognition based on physical models. (2013) In: IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2013, 26 May 2013 - 31 May 2013 (Vancouver, Canada).

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Official URL: http://dx.doi.org/10.1109/ICASSP.2013.6637757

Abstract

This article describes an audio signal processing algorithm to detect water sounds, built in the context of a larger system aiming to monitor daily activities of elderly people. While previous proposals for water sound recognition relied on classical machine learning and generic audio features to characterize water sounds as a flow texture, we describe here a recognition system based on a physical model of air bubble acoustics. This system is able to recognize a wide variety of water sounds and does not require training. It is validated on a home environmental sound corpus with a classification task, in which all water sounds are correctly detected. In a free detection task on a real life recording, it outperformed the classical systems and obtained 70% of F-measure.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6637757&tag=1
HAL Id:hal-01147995
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:04 May 2015 07:28

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