You cannot make this up!
"Neural networks may help farmers make sure their animals are happy.
... Researchers ... developed a system that interprets the moods behind a pig’s grunts and squeals.
... The authors trained convolutional neural networks to classify porcine expressions using a database of 7,414 vocal sounds made by animals engaged in 19 situations like feeding, fighting, running, or being led to a slaughterhouse.
Experts in animal behavior classified each call’s sentiment as positive or negative using the situations as guides. ...
The authors trained two ResNet-50s on spectrograms of the calls. One network classified calls as positive or negative while the other labeled the situation.
Results: The models achieved 91.5 percent accuracy classifying the sentiment of calls and 81.5 percent identifying the situation. ..."
From the abstract:
"Vocal expression of emotions has been observed across species and could provide a non-invasive and reliable means to assess animal emotions. We investigated if pig vocal indicators of emotions revealed in previous studies are valid across call types and contexts, and could potentially be used to develop an automated emotion monitoring tool. We performed an analysis of an extensive and unique dataset of low (LF) and high frequency (HF) calls emitted by pigs across numerous commercial contexts from birth to slaughter (7414 calls from 411 pigs). ... These results suggest that an automated recognition system can be developed to monitor pig welfare on-farm."
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