Optimization of Convolution Reverberation
A novel algorithm for fast convolution reverberation is proposed.
The convolution is implemented as partitioned convolution in the
frequency domain. We show that computational cost can be reduced when multiplying the spectra of the impulse response with
the spectra of the input signal by using only a fraction of the bins
of the original spectra and by discarding phase information. Reordering the bins of the spectra allows to avoid overhead incurred
by randomly accessing bins in the spectrum. The proposed algorithm is considerably faster than conventional partitioned convolution and perceptual convolution, where bins with low amplitudes
are discarded. Speed increases depend on the impulse response
used. For an impulse response of around 3 s length at 48 kHz sampling rate execution took only about 40 % of the time necessary for
conventional partitioned convolution and 61 % of the time needed
for perceptual convolution. A listening test showed that there is
only a very slight degradation in quality, which can probably be
neglected for implementations where speed is crucial. Sound samples are provided.