This paper presents a method using physical scale models as echo chambers. The proposed framework creates a partitioned convolution engine where the convolution processing is carried out physically on an up-scaled live audio stream in the model. The resulting reverberated sound is captured and down-scaled, providing the result to the user in real-time. The scale factor can be dynamically changed to explore different room sizes and the reduced dimensions of the scale model make it a tangible reverberation tool. Scale factors up to 1:5 have been tested for full bandwidth, with higher factor possible with improved hardware or in exchange for lowering the upper frequency range, primarily due to driver performance.
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https://aes2.org/publications/elibrary-page/?id=20609
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