Brevity is not a universal in animal communication: evidence for compression depends on the unit of analysis in small ape vocalizations

https://royalsocietypublishing.org/doi/10.1098/rsos.200151

This study examines compression in animal communication using AI-driven clustering techniques. Researchers applied affinity propagation clustering and support vector machines (SVMs) to analyze gibbon vocalizations, achieving 74% accuracy in predicting phrase types. While Menzerath's Law was supported, the study did not find evidence for Zipf's Law. AI methods helped uncover complex patterns in gibbon vocal communication, advancing understanding of linguistic laws in non-human species.

Royal Society Open Science)