Responses to various steady-state vowels were recorded in single units in the primary auditory cortex (AI) of the barbiturate-anaesthetized ferret. Six vowels were presented (/a/, /ɛ/, 2 different /i/’s, and 2 different /u/’s) in a natural voiced and a synthetic unvoiced mode. In addition, the responses to broadband stimuli with a sinusoidally shaped spectral envelope (called ripple stimuli) were recorded in each cell, and the response field (RF), which consists of both excitatory and inhibitory regions, was derived from the ripple transfer function. We examined whether the vowel responses could be predicted using a linear ripple analysis method [Shamma et al., Auditory Neurosci.1, 233–254 (1995)], i.e., by cross correlating the RF of the single unit, and the smoothed spectral envelope of the vowel. We found that for most AI cells (71%) the relative responses to natural vowels could be predicted on the basis of this method. Responses and prediction results for unvoiced and voiced vowels were very similar, suggesting that the spectral fine structure may not play a significant role in the neuron’s response to the vowels. Predictions on the basis of the entire RF were significantly better than based solely on best frequency (BF) (or “place”). These findings confirm the ripple analysis method as a valid method to characterize AI responses to broadband sounds as we proposed in a previous paper using synthesized spectra [Shamma and Versnel, Auditory Neurosci.1, 255–270 (1995)].