Limits...
Discerning pig screams in production environments.

Vandermeulen J, Bahr C, Tullo E, Fontana I, Ott S, Kashiha M, Guarino M, Moons CP, Tuyttens FA, Niewold TA, Berckmans D - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: M3-BIORES-Measure, Model & Manage Bioresponses, KU Leuven, Leuven, Belgium.

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.

No MeSH data available.


Ground plan of the pig compartment.Each pen had six animals, one feeder and one drinker. One microphone recorded the sound.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4414550&req=5

pone.0123111.g001: Ground plan of the pig compartment.Each pen had six animals, one feeder and one drinker. One microphone recorded the sound.

Mentions: Two trials were conducted and 24 grower pigs were used in each trial. The animals Rattlerow Seghers x Piétrain Plus, were housed at Agrivet research farm, Merelbeke, Belgium. After the battery period, they were divided into four groups of six animals (three gilts and three barrows) and each group was assigned to a pen (Fig 1). Each pen (1.60m x 2.35m) had a fully slatted concrete floor with one feeder space and one nipple drinker. The pens were located in the same compartment and were separated from each other with 1m high solid walls. So physical contact between pigs of adjacent pens was made impossible but they could still hear each other. There was ad libitum access to feed (commercial grower diet) and water during the experiment. Pigs had a timer-controlled 12-hour light period from 07:00 h to 19:00 h. The average weight of the pigs was 20.9kg (SD = 2.1) at start and 32.2kg (SD = 3.8) at end of the first trial and 31.5kg (SD = 3.4) and 43.0kg (SD = 5.5) respectively, in the second trial. The average temperature during the trials was 24.0°C (SD = 1.2). The experiment was approved by the Ethical Committee of the Faculty of Veterinary Medicine at Ghent University (EC2012/125).


Discerning pig screams in production environments.

Vandermeulen J, Bahr C, Tullo E, Fontana I, Ott S, Kashiha M, Guarino M, Moons CP, Tuyttens FA, Niewold TA, Berckmans D - PLoS ONE (2015)

Ground plan of the pig compartment.Each pen had six animals, one feeder and one drinker. One microphone recorded the sound.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4414550&req=5

pone.0123111.g001: Ground plan of the pig compartment.Each pen had six animals, one feeder and one drinker. One microphone recorded the sound.
Mentions: Two trials were conducted and 24 grower pigs were used in each trial. The animals Rattlerow Seghers x Piétrain Plus, were housed at Agrivet research farm, Merelbeke, Belgium. After the battery period, they were divided into four groups of six animals (three gilts and three barrows) and each group was assigned to a pen (Fig 1). Each pen (1.60m x 2.35m) had a fully slatted concrete floor with one feeder space and one nipple drinker. The pens were located in the same compartment and were separated from each other with 1m high solid walls. So physical contact between pigs of adjacent pens was made impossible but they could still hear each other. There was ad libitum access to feed (commercial grower diet) and water during the experiment. Pigs had a timer-controlled 12-hour light period from 07:00 h to 19:00 h. The average weight of the pigs was 20.9kg (SD = 2.1) at start and 32.2kg (SD = 3.8) at end of the first trial and 31.5kg (SD = 3.4) and 43.0kg (SD = 5.5) respectively, in the second trial. The average temperature during the trials was 24.0°C (SD = 1.2). The experiment was approved by the Ethical Committee of the Faculty of Veterinary Medicine at Ghent University (EC2012/125).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: M3-BIORES-Measure, Model & Manage Bioresponses, KU Leuven, Leuven, Belgium.

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.

No MeSH data available.