Neural Tracking of Linguistic Predictors in Spontaneous Conversational Speech

This study investigates whether neural tracking of linguistic information extends from read speech to spontaneous conversation. Using the temporal response function (TRF) framework, we validate our approach on a read-speech EEG dataset and then apply it to EEG recordings from natural conversations. We observe reliable neural tracking of key linguistic predictors, including word onset, part-of-speech surprisal, and lexical surprisal, in spontaneous speech, with effects around 200, 400, and 600 ms. These results provide new evidence that linguistic neural tracking operates in natural conversational settings and confirm the feasibility of EEG studies in ecologically valid contexts.