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Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires
by
Gentner, Timothy Q.
, Sainburg, Tim
, Thielk, Marvin
in
Acoustics
/ Algorithms
/ Animal communication
/ Animal vocalization
/ Animals
/ Auditory communication
/ Biology and Life Sciences
/ Birds
/ Chiroptera - physiology
/ Cluster Analysis
/ Comparative analysis
/ Complexity
/ Computational Biology
/ Computer applications
/ Continuity (mathematics)
/ Databases, Factual
/ Datasets
/ Engineering
/ Frequency
/ Heuristic
/ Humans
/ Latent class analysis
/ Machine learning
/ Mice
/ Neurosciences
/ Observations
/ Physical Sciences
/ Primates
/ Social Sciences
/ Software
/ Songbirds
/ Songbirds - physiology
/ Sound Spectrography
/ Spectrograms
/ Temporal variations
/ Unsupervised Machine Learning
/ Vocalization behavior
/ Vocalization, Animal - classification
/ Vocalization, Animal - physiology
/ Voice - physiology
2020
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Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires
by
Gentner, Timothy Q.
, Sainburg, Tim
, Thielk, Marvin
in
Acoustics
/ Algorithms
/ Animal communication
/ Animal vocalization
/ Animals
/ Auditory communication
/ Biology and Life Sciences
/ Birds
/ Chiroptera - physiology
/ Cluster Analysis
/ Comparative analysis
/ Complexity
/ Computational Biology
/ Computer applications
/ Continuity (mathematics)
/ Databases, Factual
/ Datasets
/ Engineering
/ Frequency
/ Heuristic
/ Humans
/ Latent class analysis
/ Machine learning
/ Mice
/ Neurosciences
/ Observations
/ Physical Sciences
/ Primates
/ Social Sciences
/ Software
/ Songbirds
/ Songbirds - physiology
/ Sound Spectrography
/ Spectrograms
/ Temporal variations
/ Unsupervised Machine Learning
/ Vocalization behavior
/ Vocalization, Animal - classification
/ Vocalization, Animal - physiology
/ Voice - physiology
2020
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Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires
by
Gentner, Timothy Q.
, Sainburg, Tim
, Thielk, Marvin
in
Acoustics
/ Algorithms
/ Animal communication
/ Animal vocalization
/ Animals
/ Auditory communication
/ Biology and Life Sciences
/ Birds
/ Chiroptera - physiology
/ Cluster Analysis
/ Comparative analysis
/ Complexity
/ Computational Biology
/ Computer applications
/ Continuity (mathematics)
/ Databases, Factual
/ Datasets
/ Engineering
/ Frequency
/ Heuristic
/ Humans
/ Latent class analysis
/ Machine learning
/ Mice
/ Neurosciences
/ Observations
/ Physical Sciences
/ Primates
/ Social Sciences
/ Software
/ Songbirds
/ Songbirds - physiology
/ Sound Spectrography
/ Spectrograms
/ Temporal variations
/ Unsupervised Machine Learning
/ Vocalization behavior
/ Vocalization, Animal - classification
/ Vocalization, Animal - physiology
/ Voice - physiology
2020
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Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires
Journal Article
Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires
2020
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Overview
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 of data in visually intuitive and quantifiable ways, enabling high-powered comparative analyses of vocal acoustics. We introduce methods for analyzing vocalizations as both discrete sequences and as continuous latent variables. Each method can be used to disentangle complex spectro-temporal structure and observe long-timescale organization in communication.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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