Hillenbrand et al. (1995) showed in a pattern recognition modeling study of American English listeners’ vowel perception that American English vowel signals are characterized by dynamic spectral properties, and that American English listeners’ vowel perception can be modeled best with American English vowel inherent dynamic spectral properties. The present study, on the other hand, investigated the production side of the vowel inherent spectral properties of American English talkers’ and Korean talkers’ English vowel signals, by fitting four different production-based pattern recognition classification models (K-Nearest Neighbors, Random Forests, Support Vector Machine and Logistic Regression) directly to American English and Korean talkers’ English vowel signals. The results showed that American English talkers’ vowel signals were best characterized by dynamic spectral properties but Korean talkers’ English vowel signals by static spectral properties. (Inha University)