Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires.

ABSTRACT: Animals produce vocalizations that range in complexity from a single repeated call to hundreds of unique vocal elements patterned in sequences unfolding over hours. Characterizing complex vocalizations can require considerable effort and a deep intuition about each species' vocal behavior. Even with a great deal of experience, human characterizations of animal communication can be affected by human perceptual biases. We present a set of computational methods for projecting animal vocalizations into low dimensional latent representational spaces that are directly learned from the spectrograms of vocal signals. We apply these methods to diverse datasets from over 20 species, including humans, bats, songbirds, mice, cetaceans, and nonhuman primates. Latent projections uncover complex features

SUBMITTER: Sainburg T 

PROVIDER: S-EPMC7591061 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature