Download Combining Zeroth and First-Order Analysis With Lagrange Polynomials to Reduce Artefacts in Live Concatenative Granulation This paper presents a technique addressing signal discontinuity and concatenation artefacts in real-time granular processing
with rectangular windowing. By combining zero-crossing synchronicity, first-order derivative analysis, and Lagrange polynomials, we can generate streams of uncorrelated and non-overlapping
sonic fragments with minimal low-order derivatives discontinuities. The resulting open-source algorithm, implemented in the
Faust language, provides a versatile real-time software for dynamical looping, wavetable oscillation, and granulation with reduced artefacts due to rectangular windowing and no artefacts
from overlap-add-to-one techniques commonly deployed in granular processing.
Download Amp-Space: A Large-Scale Dataset for Fine-Grained Timbre Transformation We release Amp-Space, a large-scale dataset of paired audio
samples: a source audio signal, and an output signal, the result of
a timbre transformation. The types of transformations we study
are from blackbox musical tools (amplifiers, stompboxes, studio
effects) traditionally used to shape the sound of guitar, bass, or
synthesizer sounds. For each sample of transformed audio, the
set of parameters used to create it are given. Samples are from
both real and simulated devices, the latter allowing for orders of
magnitude greater data than found in comparable datasets. We
demonstrate potential use cases of this data by (a) pre-training a
conditional WaveNet model on synthetic data and show that it reduces the number of samples necessary to digitally reproduce a
real musical device, and (b) training a variational autoencoder to
shape a continuous space of timbre transformations for creating
new sounds through interpolation.