  To investigate how the auditory system processes natural speech, models have
been created to relate the electroencephalography (EEG) signal of a person
listening to speech to various representations of the speech. Mainly the speech
envelope has been used, but also phonetic representations. We investigated to
which degree of granularity phonetic representations can be related to the EEG
signal. We used recorded EEG signals from 105 subjects while they listened to
fairy tale stories. We utilized speech representations, including onset of any
phone, vowel-consonant onsets, broad phonetic class (BPC) onsets, and narrow
phonetic class (NPC) onsets, and related them to EEG using forward modeling and
match-mismatch tasks. In forward modeling, we used a linear model to predict
EEG from speech representations. In the match-mismatch task, we trained a long
short term memory (LSTM) based model to determine which of two candidate speech
segments matches with a given EEG segment. Our results show that
vowel-consonant onsets outperform onsets of any phone in both tasks, which
suggests that neural tracking of the vowel vs. consonant exists in the EEG to
some degree. We also observed that vowel (syllable nucleus) onsets are better
related to EEG compared to syllable onsets. Finally, our findings suggest that
neural tracking previously thought to be associated with broad phonetic classes
might actually originate from vowel-consonant onsets rather than the
differentiation between different phonetic classes.
