Perceptual models will be developed that predict the perception of room acoustical attributes such as spaciousness, apparent source width, listener envelopment, reverberance, warmth, brilliance, clarity, transparency, and loudness. Whereas most existing approaches are based on signal statistics such as e.g., InterAural Cross Correlation (IACC), the proposed work will be based on an auditory front-end that creates a signal representation that is ‘internally’ available to the listener. Using such an internal representation allows to make a distinction between signal properties that are perceptually relevant and properties that are inaudible. This should en- able a more accurate prediction of the perception of room acoustics. Variations in room acoustical simulations will be used to create room acoustical variations of different degrees that can be evaluated by human listeners and tested against model predictions to adapt and improve the perceptual models. Here the aim will both be to accurately predict discriminability of room acoustical simulations that are close to one another (as a means to test the basic validity of the internal representations in the model) and to predict perceived room acoustical attributes such as envelopment, reverberance, etc. The role of head orientation in the perception of room acoustical perceptual attributes will be investigated by listening tests and in the perceptual models developed.