A two-stage model aligns intracranial EEG signals with text embeddings and reconstructs the semantic content of perceived speech from as little as 30 minutes of neural data.
Brain decoding: to- ward real-time reconstruction of visual perception,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Neuro2Semantic: A Transfer Learning Framework for Semantic Reconstruction of Continuous Language from Human Intracranial EEG
A two-stage model aligns intracranial EEG signals with text embeddings and reconstructs the semantic content of perceived speech from as little as 30 minutes of neural data.