To achieve the goal of a perceptual fusion between the auralization of virtual audio objects in the room acoustics of a real listening room, an adequate adaptation of the virtual acoustics to the real room acoustics is necessary. The challenges are to describe the acoustics of different rooms by suitable parameters, to classify different rooms, and to evoke a similar auditory perception between acoustically similar rooms. An approach is presented to classify rooms based on measured BRIRs using statistical methods and to select best match BRIRs from the dataset to auralize audio objects in a new room. The results show that it is possible to separate rooms based on their room acoustic properties, that the separation also corresponds to a large extent to the perceptual distance between rooms, and that a selection of best match BRIRs is possible.
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