Decoding of the speech envelope using the VLAAI deep neural network. (Unofficial) PyTorch implementation.
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This repository contains a pre-trained subject-independent model that can decode the speech envelope from EEG signals. The model was presented in the paper: Decoding of the speech envelope using the VLAAI deep neural network
by Bernd Accou, Jonas Vanthornhout, Hugo Van hamme, and Tom Francart.
This repository contains an unofficial PyTorch implementation of the VLAAI network.
Pre-trained model versions (using the preprocessing and dataset ( single-speaker stories dataset, 85 subjects that listened to 1 hour and 46 minutes on average for a total of 144 hours of EEG data) in the paper) are available in the pretrained_models folder.
Original TensorFlow implementation: Here