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Science

Decoding emotions in seven hoofed species with AI

Phys Org
Summary
Nutrition label

89% Informative

Researchers from the University of Copenhagen have successfully trained a machine-learning model to distinguish between positive and negative emotions in seven different ungulate species.

By analyzing the acoustic patterns of their vocalizations, the model achieved an impressive accuracy of 89.49% .

The research offers insights into the evolutionary origins of human language and could reshape our understanding of animal emotions.

VR Score

92

Informative language

97

Neutral language

6

Article tone

informal

Language

English

Language complexity

86

Offensive language

not offensive

Hate speech

not hateful

Attention-grabbing headline

not detected

Known propaganda techniques

not detected

Time-value

long-living

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