The human ability to understand speech across an enormous range of listening conditions is underpinned by a hierarchical auditory processing system whose successive stages process increasingly complex attributes of the acoustic input. In order to produce a categorical perception of words and phonemes, it has been suggested that, while earlier areas of the auditory system undoubtedly respond to acoustic differences in speech tokens, later areas must exhibit consistent neural responses to those tokens. Neural indices of such hierarchical processing in the context of continuous speech have been identified using low-frequency scalp-recorded electroencephalography (EEG) data. The relationship between continuous speech and its associated neural responses has been shown to be best described when that speech is represented using both its low-level spectrotemporal information and also the categorical labelling of its phonetic features (Di Liberto et al., submitted). While the phonetic features have been proven to carry extra-information not captured by the speech spectrotemporal representation, the causes of this EEG activity remain unclear. This study aims to demonstrate a framework for examining speech-specific processing and for disentangling high-level neural activity related to intelligibility from low-level activity in response to spectrotemporal fluctuations of speech. Preliminary results suggest that neural measure of processing at the phonetic level can be isolated.