Onset times of resonant energy pulses are measured with the high-resolution Teager operator and used as features in the Reynolds Gaussian-mixture speaker identification algorithm. Feature sets are constructed with primary pitch and secondary pulse locations derived from low and high speech formants. Preliminary testing was performed with a confusable 40-speaker subset from the NTIMIT (telephone channel) database. Speaker identification improved from 55 to 70% correct classification when the full set of new resonant energy-based features were added as an independent stream to conventional mel-cepstra.