REDUCING ARTIFICIAL REVERBERATION REQUIREMENTS
USING TIME-VARIANT FEEDBACK DELAY NETWORKS

Abstract of a Master's Research Project at the University of Miami.

Research project supervised by Professor William Pirkle.

Abstract:

Most of the recently published artificial reverberation algorithms rely on a time-invariant feedback delay network (FDN) to generate their late reverberation.  To achieve a high-quality reverberation algorithm, the FDN order must be quite high, requiring a good amount of memory storage and processing power.  However, in applications where memory and computational resources are limited such as hardware synthesizers or gaming platforms, it is desirable to achieve a good sounding reverberation.  This thesis proposes the use of time-variant delay lengths to maintain the quality of the reverberation tail of an FDN, which reduces the algorithm’s processing time and memory requirements.  Several modulators are evaluated in combination with several interpolation types for fractional delay interpolation.  Finally, the computation efficiency and memory usage of the time-variant reverberation algorithms are compared with the equivalent quality, higher order, time-invariant algorithms.