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.
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 algorithmís 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.
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