Data from: Unsupervised discovery of family specific vocal usage in the Mongolian gerbil

In nature, animal vocalizations can provide crucial information about
identity, including kinship and hierarchy. However, lab-based vocal
behavior is typically studied during brief interactions between animals
with no prior social relationship, and under environmental conditions with
limited ethological relevance. Here, we address this gap by establishing
long-term acoustic recordings from Mongolian gerbil families, a core
social group that uses an array of sonic and ultrasonic vocalizations.
Three separate gerbil families were transferred to an enlarged environment
and continuous 20-day audio recordings were obtained. Using a variational
autoencoder (VAE) to quantify 583,237 vocalizations, we show that gerbils
exhibit a more elaborate vocal repertoire than has been previously
reported and that vocal repertoire usage differs significantly by family.
By performing gaussian mixture model clustering on the VAE latent space,
we show that families preferentially use characteristic sets of vocal
clusters and that these usage preferences remain stable over weeks.
Furthermore, gerbils displayed family-specific transitions between vocal
clusters. Since gerbils live naturally as extended families in complex
underground burrows that are adjacent to other families, these results
suggest the presence of a vocal dialect which could be exploited by
animals to represent kinship. These findings position the Mongolian gerbil
as a compelling animal model to study the neural basis of vocal
communication and demonstrates the potential for using unsupervised
machine learning with uninterrupted acoustic recordings to gain insights
into naturalistic animal behavior.