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Found 4 papers, 2 papers with code
Relating EEG to continuous speech using deep neural networks: a review
Linear models are presently used to relate the EEG recording to the corresponding speech signal.
Self-supervised enhancement of stimulus-evoked brain response data
We propose a novel paradigm for the self-supervised enhancement of stimulus-related brain response data.
Extracting Different Levels of Speech Information from EEG Using an LSTM-Based Model
Decoding the speech signal that a person is listening to from the human brain via electroencephalography (EEG) can help us understand how our auditory system works.
Predicting speech intelligibility from EEG in a non-linear classification paradigm
The accuracy of the model's match/mismatch predictions can be used as a proxy for speech intelligibility without subject-specific (re)training.
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