218 citations · 294 across the 6 of their papers we have counts for
6 papers
NeuralSet: A High-Performing Python Package for Neuro-AI
Jean-Rémi King, Corentin Bel, Linnea Evanson +25
Artificial intelligence (AI) is increasingly central to understanding how the brain processes information. However, the integration of neuroscience and modern AI is bottlenecked by…
Decoding speech perception from non-invasive brain recordings
Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin +2
Decoding speech from brain activity is a long-awaited goal in both healthcare and neuroscience. Invasive devices have recently led to major milestones in that regard: deep learning…
Toward a realistic model of speech processing in the brain with self-supervised learning
Juliette Millet, Charlotte Caucheteux, Pierre Orhan +5
Several deep neural networks have recently been shown to generate activations similar to those of the brain in response to the same input. These algorithms, however, remain largely…
Long-range and hierarchical language predictions in brains and algorithms
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Deep learning has recently made remarkable progress in natural language processing. Yet, the resulting algorithms remain far from competing with the language abilities of the human…
Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects
Charlotte Caucheteux, Alexandre Gramfort, Jean-Rémi King
A popular approach to decompose the neural bases of language consists in correlating, across individuals, the brain responses to different stimuli (e.g. regular speech versus scram…
Disentangling Syntax and Semantics in the Brain with Deep Networks
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
The activations of language transformers like GPT-2 have been shown to linearly map onto brain activity during speech comprehension. However, the nature of these activations remain…