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Charlotte Caucheteux

3 accepted papers

2022

Toward a realistic model of speech processing in the brain with self-supervised learning

NeurIPS 2022accept

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 implausible: they require (1) extraordinarily large amounts of data, (2) unobtainable supervised labels, (3) textual ra…

Cited by 154SourcePDFScholar
2021

Disentangling syntax and semantics in the brain with deep networks

ICML 2021spotlight

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 remains largely unknown and presumably conflate distinct linguistic classes. Here, we propose a taxonomy to factorize the high…

2021

Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects

EMNLP 2021finding

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). Although successful, this ‘model-free’ approach necessitates the acquisition of a…

Cited by 41SourcePDFScholar