Computationally efficient modeling of room responses is needed in many audio and acoustics applications such as auralization, artificial reverberation, and equalization of loudspeaker-room responses for sound reproduction. Digital filtering is an efficient means for such modeling particularly in real-time implementations. In this paper we discuss new DSP-based methods to model measured room responses. Pole-zero modeling of dense modal patterns and temporal details is achieved by frequency-zooming ARMA modeling, i.e., by subband and multirate techniques. Another method is Kautz filtering that is attractive due to its orthonormal properties. The optimization of model filter parameters is discussed, the performance achieved is shown by example cases, and applications are shortly reviewed.
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