Efficient Signal Extrapolation by Granulation and Convolution with Velvet Noise

Authors
Stefano D'Angelo1, Leonardo Gabrielli2
Status
Published in Proceedings of the 21st International Conference on Digital Audio Effects (DAFx-18), pp. 107–112, Aveiro, Portugal, September 2018
1
Independent researcher, Agropoli, Italy
2
Università Politecnica delle Marche, Ancona, Italy
BibTeX
@inproceedings{dangelo2018freeze,
  title={Efficient Signal Extrapolation by Granulation and Convolution with Velvet Noise},
  author={Gabrielli, Leonardo and D'Angelo, Stefano},
  booktitle={Proc. 21\textsuperscript{st} Intl. Conf. Digital Audio Effects (DAFx-18)},
  pages={107--112},
  month={September},
  year={2018},
  address={Aveiro, Portugal}
}

Abstract

Several methods are available nowadays to artificially extend the duration of a signal for audio restoration or creative music production purposes. The most common approaches include overlap-andadd (OLA) techniques, FFT-based methods, and linear predictive coding (LPC). In this work we describe a novel OLA algorithm based on convolution with velvet noise, in order to exploit its sparsity and spectrum flatness. The proposed method suppresses spectral coloration and achieves remarkable computational efficiency. Its issues are addressed and some design choices are explored. Experimental results are proposed and compared to a well-known FFT-based method.

Implementation

Sound samples