The categorization of voice into quality type (ie, normal, breathy, hoarse, rough) is often a traditional part of the voice diagnostic. The goal of this study was to assess the contributions of various time and spectral-based acoustic measures to the categorization of voice type for a diverse sample of voices collected from both functionally dysphonic (breathy, hoarse, and rough) (n=83) and normal women (n=51). Before acoustic analyses, 12 judges rated all voice samples for voice quality type. Discriminant analysis, using the modal rating of voice type as the dependent variable, produced a 5-variable model (comprising time and spectral-based measures) that correctly classified voice type with 79.9% accuracy (74.6% classification accuracy on cross-validation). Voice type classification was achieved based on two significant discriminant functions, interpreted as reflecting measures related to "Phonatory Instability" and "F(0) Characteristics." A cepstrum-based measure (CPP/EXP ratio) consistently emerged as a significant factor in predicting voice type; however, variables such as shimmer (RMS dB) and a measure of low- vs. high-frequency spectral energy (the Discrete Fourier Transformation ratio) also added substantially to the accurate profiling and prediction of voice type. The results are interpreted and discussed with respect to the key acoustic characteristics that contributed to the identification of specific voice types, and the value of identifying a subset of time and spectral-based acoustic measures that appear sensitive to a perceptually diverse set of dysphonic voices.