AI decodes oinks and grunts to keep pigs happy

The AI algorithm demonstrated that pigs kept in outdoor, free-range or organic farms with the ability to roam and dig in the dirt produced fewer stress calls than conventionally raised pigs.

European scientists have developed an artificial intelligence (AI) algorithm capable of interpreting pig sounds, aiming to create a tool that can help farmers improve animal welfare.

The algorithm could potentially alert farmers to negative emotions in pigs, thereby improving their well-being, according to Elodie Mandel-Briefer, a behavioural biologist at University of Copenhagen who is co-leading the study.

The scientists, from universities in Denmark, Germany, Switzerland, France, Norway and the Czech Republic, used thousands of recorded pig sounds in different scenarios, including play, isolation and competition for food, to find that grunts, oinks, and squeals reveal positive or negative emotions.

While many farmers already have a good understanding of the well-being of their animals by watching them in the pig pen, existing tools mostly measure their physical condition, said Mandel-Briefer.

"Emotions of animals are central to their welfare, but we don't measure it much on farms," she said.

The algorithm demonstrated that pigs kept in outdoor, free-range or organic farms with the ability to roam and dig in the dirt produced fewer stress calls than conventionally raised pigs. The researchers believe that this method, once fully developed, could also be used to label farms, helping consumers make informed choices.

"Once we have the tool working, farmers can have an app on their phone that can translate what their pigs are saying in terms of emotions," Mandel-Briefer said.

Short grunts typically indicate positive emotions, while long grunts often signal discomfort, such as when pigs push each other by the trough. High-frequency sounds like screams or squeals usually mean the pigs are stressed, for instance, when they are in pain, fight, or are separated from each other.

The scientists used these findings to create an algorithm that employs AI.

"Artificial intelligence really helps us to both process the huge amount of sounds that we get, but also to classify them automatically," Mandel-Briefer said.