Classification of English vowels using speech evoked potentials.

The objective of this study is to investigate whether Speech Evoked Potentials (SpEPs), which are auditory brainstem responses to speech stimuli, contain information that can be used to distinguish different speech stimuli. Previous studies on brainstem SpEPs show that they contain valuable information about auditory neural processing. As such, SpEPs may be useful for the diagnosis of central auditory processing disorders and language disability, particularly in children. In this work, we examine the spectral amplitude information of both the Envelope Following Response, which is dominated by spectral components at the fundamental (F0) and its harmonics, and Frequency Following Response, which is dominated by spectral components in the region of the first formant (F1), of SpEPs in response to the five English language vowels (\a\,\e\,\ae\,\i\,\u\). Using spectral amplitude features, a classification accuracy of 78.3% is obtained with a linear discriminant analysis classifier. Classification of SpEPs demonstrates that brainstem neural responses in the region of F0 and F1 contain valuable information for discriminating vowels. This result provides an insight into human auditory processing of speech, and may help develop improved methods for objectively assessing central hearing impairment.