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Recognising behaviourally relevant pig vocalisations for welfare assessment via a lightweight deep acoustic model | Synapse
March 3, 2026
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Recognising behaviourally relevant pig vocalisations for welfare assessment via a lightweight deep acoustic model
YL
Yingying Lv
YL
Yan Liu
Zhejiang Chinese Medical University
YS
Yuzhen Song
Henan Institute of Science and Technology
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Puntos clave
Pig vocalisations indicate behavioural signals related to welfare, helping assess animal conditions.
A lightweight deep acoustic model was used to classify vocalisations, achieving high accuracy rates of up to 90%.
The analysis employed deep learning techniques to interpret vocal patterns, focusing on distinguishing relevant sounds.
Improving animal welfare assessments can enhance farming practices, indicating a need for broader application of acoustic monitoring.
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Lv et al. (Tue,) studied this question.
synapsesocial.com/papers/69a760a5c6e9836116a2d961
https://doi.org/https://doi.org/10.1016/j.applanim.2026.106936