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ab masters diss
1. An EEG Study of Speech Processing and Speech Segmentation in Artificial
Language.
Abstract
The current study aimed to address current work (Hickok, 2014) which has diluted the involvement
of phoneme-level speech processing to a somatosensory-motor dorsal stream. Presenting
phonemes as more involved in hitting vocal targets than perceiving them; in comparison to syllables.
Electroencephalography was used to measure mis-match negativity between deviant non-word
stimuli that altered at the phoneme (Näätänen, Paavilainen, Rinne & Alho, 2007) and Hickok’s
(2014) unaddressed demi-syllable processing level within an Oddball Roving Paradigm (Metze,
2013). Phonetic deviations in did not present a true MMN response, despite presenting a significant
result at 200-300ms (p=0.05) and 400-500ms (p=0.031) after deviant word onset. Demi-syllables
did however present a traditional MMN at 100-200ms (p= 0.047). Speech segmentation and
transitional probabilities (TPs) amongst phonemes and syllables (Saffran, Aslin & Newport, 1996;
Hickok, 2014) were also assessed in a separate behavioural study. Which found a measureable
response in the amount of correctly identified words within the phoneme (54.17%) and syllable
condition (54.49%), which presented no significant difference (p=0.946). The current study
addresses future avenues of research by highlighting possible implications for vowel and consonant
phonetic shifts, and how this could affect simple and complex onsets/codas within demi-syllable
stimuli.
The University of Bristol, School of Experimental Psychology.
14 / 09 / 2015
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