Granular sounds are commonly used in video games but the conventional approach of using recorded samples does not allow sound designers to modify these sounds. In this paper we present a technique to synthesize granular sound whose tone color lies at an arbitrary point between two given granular sound samples. We first extract grains and noise profiles from the recordings, morph between them and finally synthesize sound using the morphed data. During sound synthesis a number of parameters, such as the number of grains per second or the loudness distribution of the grains, can be altered to vary the sound. The proposed method does not only allow to create new sounds in real-time, it also drastically reduces the memory footprint of granular sounds by reducing a long recording to a few hundred grains of a few milliseconds length each.

Download

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.

Download