1 code implementation • 25 Aug 2022 • Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin, Ori Kabeli, Jean-Rémi King
Overall, this effective decoding of perceived speech from non-invasive recordings delineates a promising path to decode language from brain activity, without putting patients at risk for brain surgery.
no code implementations • 3 Jun 2022 • Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
These elements, resulting from the largest neuroimaging benchmark to date, show how self-supervised learning can account for a rich organization of speech processing in the brain, and thus delineate a path to identify the laws of language acquisition which shape the human brain.
no code implementations • 28 Nov 2021 • Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Predictive coding theory offers a potential explanation to this discrepancy: while deep language algorithms are optimized to predict adjacent words, the human brain would be tuned to make long-range and hierarchical predictions.
no code implementations • Findings (EMNLP) 2021 • 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 scrambled words, sentences, or paragraphs).
no code implementations • 2 Mar 2021 • 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.