AIMC Topic: Vocalization, Animal

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Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires.

eLife
Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from ...

Analysis of ultrasonic vocalizations from mice using computer vision and machine learning.

eLife
Mice emit ultrasonic vocalizations (USVs) that communicate socially relevant information. To detect and classify these USVs, here we describe VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect U...

Automatic classification of mice vocalizations using Machine Learning techniques and Convolutional Neural Networks.

PloS one
Ultrasonic vocalizations (USVs) analysis is a well-recognized tool to investigate animal communication. It can be used for behavioral phenotyping of murine models of different disorders. The USVs are usually recorded with a microphone sensitive to ul...

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

PLoS computational biology
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 intui...

Learning to localize sounds in a highly reverberant environment: Machine-learning tracking of dolphin whistle-like sounds in a pool.

PloS one
Tracking the origin of propagating wave signals in an environment with complex reflective surfaces is, in its full generality, a nearly intractable problem which has engendered multiple domain-specific literatures. We posit that, if the environment a...

Statistical learning of transition patterns in the songbird auditory forebrain.

Scientific reports
Statistical learning of transition patterns between sounds-a striking capability of the auditory system-plays an essential role in animals' survival (e.g., detect deviant sounds that signal danger). However, the neural mechanisms underlying this capa...

Assessment of Laying Hens' Thermal Comfort Using Sound Technology.

Sensors (Basel, Switzerland)
Heat stress is one of the most important environmental stressors facing poultry production and welfare worldwide. The detrimental effects of heat stress on poultry range from reduced growth and egg production to impaired health. Animal vocalisations ...

Comparing context-dependent call sequences employing machine learning methods: an indication of syntactic structure of greater horseshoe bats.

The Journal of experimental biology
For analysis of vocal syntax, accurate classification of call sequence structures in different behavioural contexts is essential. However, an effective, intelligent program for classifying call sequences from numerous recorded sound files is still la...

Robust sound event detection in bioacoustic sensor networks.

PloS one
Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record sounds of wildlife over long periods of time in scalable and minimally invasive ways. Deriving per-species abundance estimates from these sensors requires detection...

Quantifying ultrasonic mouse vocalizations using acoustic analysis in a supervised statistical machine learning framework.

Scientific reports
Examination of rodent vocalizations in experimental conditions can yield valuable insights into how disease manifests and progresses over time. It can also be used as an index of social interest, motivation, emotional development or motor function de...