Room reverberation consists of a multitude of reflections from surfaces and objects in a room. Particularly the late reverberation tail resembles noise with an exponential decay envelope. Artificial reverberation algorithms try to simulate this in a computationally efficient manner. Some proposed algorithms are based on the convolution with a sparse FIR filter corresponding to a randomized sparse sequence of unit impulses. In this paper we search for such sequences with minimal impulse density vs. maximal smoothness of the noise-like characteristics. Such noise is called here "velvet noise', because it can sound smoother than the Gaussian noise. The perceptual characteristics of velvet noise are described by results from listening experiments and auditory analysis. Reverb algorithms based on velvet noise are discussed and analyzed.
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