Speech is central to human life. As such, any delay or impairment in receptive speech processing can have a profoundly negative impact on the social and professional life of a person. Thus, being able to assess the integrity of speech processing in different populations is an important goal. Current standardized assessment is mostly based on psychometric measures that do not capture the full extent of a person's speech processing abilities and that are difficult to administer in some subjects groups. A potential alternative to these tests would be to derive “direct”, objective measures of speech processing from cortical activity. One such approach was recently introduced and showed that it is possible to use electroencephalography (EEG) to index cortical processing at the level of phonemes from responses to continuous natural speech. However, a large amount of data was required for such analyses. This limits the usefulness of this approach for assessing speech processing in particular cohorts for whom data collection is difficult. Here, we used EEG data from 10 subjects to assess whether measures reflecting phoneme-level processing could be reliably obtained using only 10 min of recording time from each subject. This was done successfully using a generic modeling approach wherein the data from a training group composed of 9 subjects were combined to derive robust predictions of the EEG signal for new subjects. This allowed the derivation of indices of cortical activity at the level of phonemes and the disambiguation of responses to specific phonetic features (e.g., stop, plosive, and nasal consonants) with limited data. This objective approach has the potential to complement psychometric measures of speech processing in a wide variety of subjects.