A classification scheme for acoustical room responses

Room acoustical modes, particularly in small rooms, cause a significant variation in the room responses measured at different locations. Responses measured only a few cm apart can vary by up to 15-20 dB at certain frequencies. This makes it difficult to equalize an audio system for multiple simultaneous listeners. Previous methods have utilized multiple microphones and spatial averaging with equal weighting. We determine representative prototypical room responses derived from several room responses that share similar characteristics. We present a fuzzy unsupervised technique for finding similarities between room responses by clustering the room responses, and determining their prototypical responses. These prototypical responses can then be combined to form a general point response. When we use the inverse of the general point response as an equalizing filter, our results show a significant improvement in equalization performance over single point equalization and spatial averaging methods. Our method also allows a unique determination of the optimal number of representatives that are required for a given set of room responses. Applications of this method thus include equalization and multiple point sound control at home and in automobiles