Velvet noise in audio processing

Noise plays a central role in various audio-processing applications, including artificial reverberation, audio decorrelation, acoustical measurements, sound synthesis, and speech processing. This dissertation focuses on applications of sparse noise, known as velvet noise. With its minimal density and smooth temporal envelope, velvet noise has been widely used in artificial reverberation algorithms, both as a core component as well as a decorrelating or diffusing element. The work within builds on this foundation by exploring novel variants and applications of velvet noise. The thesis introduces dark velvet noise as a low-passed variant, generalizes this to extended dark velvet noise for accurate modeling of non-exponential late-reverberation, and culminates in developing the binaural dark-velvet-noise reverberator. Additionally, short velvet noise filters are explored for decorrelation and variation filtering tasks, demonstrating their effectiveness in lowering inter channel correlation within feedback delay networks through velvet feedback matrices and generating realistic variations of sampled percussive sounds. The contributions of this thesis offer significant advances in applying velvet noise to audio processing, with particular emphasis on artificial reverberation and decorrelation.