AIMC Topic: Vocalization, Animal

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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...

DeepSqueak: a deep learning-based system for detection and analysis of ultrasonic vocalizations.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Rodents engage in social communication through a rich repertoire of ultrasonic vocalizations (USVs). Recording and analysis of USVs has broad utility during diverse behavioral tests and can be performed noninvasively in almost any rodent behavioral m...

Resource-Efficient Pet Dog Sound Events Classification Using LSTM-FCN Based on Time-Series Data.

Sensors (Basel, Switzerland)
The use of IoT (Internet of Things) technology for the management of pet dogs left alone at home is increasing. This includes tasks such as automatic feeding, operation of play equipment, and location detection. Classification of the vocalizations of...

Interhemispheric dominance switching in a neural network model for birdsong.

Journal of neurophysiology
Male zebra finches produce a sequence-invariant set of syllables, separated by short inspiratory gaps. These songs are learned from an adult tutor and maintained throughout life, making them a tractable model system for learned, sequentially ordered ...

Supervised learning in spiking neural networks with FORCE training.

Nature communications
Populations of neurons display an extraordinary diversity in the behaviors they affect and display. Machine learning techniques have recently emerged that allow us to create networks of model neurons that display behaviors of similar complexity. Here...

Characterizing Vocal Repertoires--Hard vs. Soft Classification Approaches.

PloS one
To understand the proximate and ultimate causes that shape acoustic communication in animals, objective characterizations of the vocal repertoire of a given species are critical, as they provide the foundation for comparative analyses among individua...

Call category classification of the isolation-induced ultrasonic vocalizations emitted by BTBR TItpr3/J mouse pups exposed to different perinatal diets.

Brain research
Autism spectrum disorder (ASD) is characterized by deficits in social communication and repetitive behaviors/restricted interests that may be diagnosed as early as 2 years of age. This suggests that the pathology underlying the disorder is present du...