Optimization of Convolution Reverberation

Sadjad Siddiq
DAFx-2020 - Vienna (virtual)
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.