Conformer-Based Neural Speech Decoding from Intracranial EEG Signals
Létrehozó:
Shende, Ayush
Al-Radhi, Mohammed Sala
Dátum:
2026-05-27T09:22:04Z
2026
Tartalmi leírás:
Decoding speech from neural activity is a central challenge in brain–computer interface research, with the potential to restore communication for individuals with severe speech or motor impairments. Intracranial EEG (iEEG) recordings provide high temporal and spectral resolution, making them particularly suitable for neural speech decoding. A commonly used and reproducible baseline for this task is linear regression from neural features to acoustic representations
