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A key limitation of current hearing devices is the lack of user feedback to determine what speech content is actually being registered by the brain. To provide an objective measure of this cognitive processing for future brain-steered hearing devices, this study develops a brain-to-language model capable of decoding semantic-like information directly from non-invasive electroencephalography (EEG)
