Pig vocalisations convey information about their current state of health and welfare. Continuously monitoring these vocalisations can provide useful information for the farmer. For instance, pig screams can indicate stressful situations. When monitoring screams, other sounds can interfere with scream detection. Therefore, identifying screams from other sounds is essential. The objective of this study was to understand which sound features define a scream. Therefore, a method to detect screams based on sound features with physical meaning and explicit rules was developed. To achieve this, 7 hours of labelled data from 24 pigs was used. The developed detection method attained 72% sensitivity, 91% specificity and 83% precision. As a result, the detection method showed that screams contain the following features discerning them from other sounds: a formant structure, adequate power, high frequency content, sufficient variability and duration.

Discerning pig screams in production environments / J. Vandermeulen, C. Bahr, E. Tullo, I. Fontana, S. Ott, M. Kashiha, M. Guarino, C.P.H. Moons, F.A.M. Tuyttens, T.A. Niewold, D. Berckmans. - In: PLOS ONE. - ISSN 1932-6203. - 10:4(2015 Apr 29), pp. 0123111.1-0123111.15. [10.1371/journal.pone.0123111]

Discerning pig screams in production environments

E. Tullo;I. Fontana;M. Guarino;
2015

Abstract

Pig vocalisations convey information about their current state of health and welfare. Continuously monitoring these vocalisations can provide useful information for the farmer. For instance, pig screams can indicate stressful situations. When monitoring screams, other sounds can interfere with scream detection. Therefore, identifying screams from other sounds is essential. The objective of this study was to understand which sound features define a scream. Therefore, a method to detect screams based on sound features with physical meaning and explicit rules was developed. To achieve this, 7 hours of labelled data from 24 pigs was used. The developed detection method attained 72% sensitivity, 91% specificity and 83% precision. As a result, the detection method showed that screams contain the following features discerning them from other sounds: a formant structure, adequate power, high frequency content, sufficient variability and duration.
Settore AGR/10 - Costruzioni Rurali e Territorio Agroforestale
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/344338
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