The purpose of this study was to apply Self-Organizing Maps to differentiate between the correct and the incorrect allophone pronunciations and to compare the results with subjective evaluation. Recordings of a list of target words, containing selected allophones of English plosive consonants, the velar nasal and the lateral consonant, were made twice. First, the target words were read from the list by nine non-native speakers and then repeated after a phonology expert’s recorded sample. Afterwards, two recorded signal sets were segmented into allophones and parameterized. For that purpose, a set of descriptors, commonly employed in music information retrieval, was utilized to determine whether they are effective in allophone analysis. The phonology expert’s task was to evaluate the pronunciation accuracy of each uttered allophone. Extracted feature vectors along with the assigned ratings were applied to SOMs.
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