Have you ever wondered what a pig is trying to emote when it grunts? We can now decode pigs’ emotions as an international team of researchers has translated pig grunts into the emotions they appear to express.
International effort
Sixteen researchers from Denmark, Switzerland, France, Germany, Norway, and the Czech Republic participated in a study that translated pig grunts into emotions across different conditions and life stages. The results of this research, which was led by the University of Copenhagen, the ETH Zurich, and France’s National Research Institute for Agriculture, Food and Environment, were published early in March in Scientific Reports.
Pig sounds were recorded both in commercial and experimental scenarios. With 7,414 recorded sounds from 411 pigs in different scenarios from birth to death, the researchers could then design a machine learning algorithm that decoded whether an individual pig is experiencing a positive emotion, a negative one, or ever something in between.
The scientists were able to ascertain that high-frequency calls such as screams and squeals were more common in negative situations. Barks, grunts, and other low-frequency calls, however, occurred both in situations where a pig experienced positive or negative emotions.
The sound files were then analysed even more thoroughly and the researchers were able to find a new pattern that revealed in further detail what pigs experienced. Researchers were able to show that the calls were far shorter with minor amplitude fluctuations in positive situations.
Mental health of animals
Even though it is widely accepted today that the mental health of livestock is important for their overall well-being. studying animal emotions still remains a relatively new field. While farmers are equipped with systems to monitor an animal’s physical health automatically, such systems for monitoring mental health are yet to be developed.
This study’s researchers believe that their algorithm could be a first step towards a platform that will enable farmers to keep an eye on the psychological well-being of animals. They also hope that with enough data the algorithm could be trained to understand the emotions of other mammals as well.
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