Etienne Thoret

The paper quantifies the edge effect on tropical fauna using ecoacoustic metrics and shows acoustic diversity decreases 100 m from forest edges, with specific indices detecting this effect.

This study uses a deep neural network to create a voice latent space that maps to auditory cortex activity, showing it better represents speaker identity than primary auditory cortex.

This study shows that neurons in the macaque anterior temporal lobe encode voice identity invariance through dynamic representations, highlighting the ATL's role in integrating perceptual voice features into identity representations.

The paper investigates auditory hemispheric asymmetry, proposing that it supports the categorization of sounds based on actions and objects through differential processing of temporal and spectral acoustic modulations.

This paper detects sleep deprivation using voice analysis with machine learning, identifying two distinct vocal biomarkers: prosody and timbre changes, which vary individually.

This study compares auditory and tactile perception of roughness using similar stimuli and finds similar sensory processing characteristics in both modalities.

The paper investigates whether geometric prototypes can be recalled through auditory cues, finding a common elliptic prototype across auditory, visual, and motor modalities.

The paper introduces a method to interpret machine-learning classifiers by analyzing how noise and reverse correlation affect classification decisions across various data types and models.