Echo State Networks for Real-Time Audio Applications

  • Authors:

  • Stefano Squartini;Stefania Cecchi;Michele Rossini;Francesco Piazza

  • Affiliations:

  • A3Lab, DEIT, Universitá Politecnica delle Marche, Via Brecce Bianche 31, 60131 Ancona, Email: a3lab@.deit.univpm.it, Italy;A3Lab, DEIT, Universitá Politecnica delle Marche, Via Brecce Bianche 31, 60131 Ancona, Email: a3lab@.deit.univpm.it, Italy;A3Lab, DEIT, Universitá Politecnica delle Marche, Via Brecce Bianche 31, 60131 Ancona, Email: a3lab@.deit.univpm.it, Italy;A3Lab, DEIT, Universitá Politecnica delle Marche, Via Brecce Bianche 31, 60131 Ancona, Email: a3lab@.deit.univpm.it, Italy

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
  • Year:
  • 2007

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Abstract

This paper deals with the employment of Echo State Networks for identification of nonlinear dynamical systems in the digital audio field. The real contribution of the work is that such networks have been implemented and run in real-time on a specific PC based software platform for the first time, up to the authors' knowledge. The nonlinear dynamical systems to be identified in the audio applications here addressed are the mathematical model of a commercial Valve Amplifier and the low-frequency response of a loud-speaker. Experimental results have shown that, at a certain frequency sampling rate, the ESNs considered (after the training procedure performed off-line) are able to tackle the real-time tasks successfully.