Scientists have successfully trained an automatic learning model to distinguish between emotions positive and negative in seven species of ungulatesincluding cows, pigs and wild boars.
When analyzing the acoustic patterns of their vocalizations, the model achieved an impressive precision of 89.49%, which marks the first study between species to detect emotional valence, in psychology, intrinsic appeal or the aversion of an event, object or situation, using AI (artificial intelligence).
“This advance provides solid evidence that AI can decode emotions in multiple species based on vocal patterns. It has the potential to revolutionize animal welfare, livestock and conservation, allowing us Author of the study, which is published in the magazine Iscience.
AI as a universal translator of animal emotions
When analyzing thousands of vocalizations of anointed in different emotional states, the researchers identified key acoustic indicators of emotional Valencia. The most important predictors of whether an emotion was positive or negative included changes in the duration, the distribution of energy, the fundamental frequency and the modulation of the amplitude. Surprisingly, these patterns were somewhat consistent in all species, which suggests that the fundamental vocal expressions of emotions are preserved evolutionarily.
Study findings have long -range implications. The classification model driven by AI could be used to develop automated tools for real -time monitoring of animals emotions, transforming the way we address cattle management, veterinary care and conservation efforts.
Briefer explains: “Understanding how animals express emotions can help us improve their well -being. If we can detect stress or discomfort early, we can intervene before intensifying. Likewise, we could also promote positive emotions. This would be a Radical change for animal welfare. “
Key findings include:
- High precision: the AI model classified the emotional valence with a general precision of 89.49 %, demonstrating its great ability to distinguish between positive and negative states.
- Universal acoustic patterns: The key predictors of emotional valence were consistent in all species, indicating an evolutionarily preserved emotional expression system.
- New perspectives on emotional communication: This research offers information on the evolutionary origins of human language and could change our understanding of animal emotions.
This study brings us one more step to a future in which technology allows us to understand and respond to the emotions of animals, which offers new and exciting possibilities for science, animal well -being and conservation, according to the authors.
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