A bio-inspired geometric model for sound reconstruction
Abstract The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of this study is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is insp...
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2021-01-01
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Series: | Journal of Mathematical Neuroscience |
Online Access: | https://doi.org/10.1186/s13408-020-00099-4 |
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doaj-18308d5049da4fd699f1d6bd48af21e32021-01-10T12:55:42ZengSpringerOpenJournal of Mathematical Neuroscience2190-85672021-01-0111111810.1186/s13408-020-00099-4A bio-inspired geometric model for sound reconstructionUgo Boscain0Dario Prandi1Ludovic Sacchelli2Giuseppina Turco3CNRS, LJLL, Sorbonne Université, Université de Paris, InriaUniversité Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des signaux et systèmesUniversité Lyon, Université Claude Bernard Lyon 1, CNRS, LAGEPP UMR 5007CNRS, Laboratoire de Linguistique Formelle, UMR 7110, Université de ParisAbstract The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of this study is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is inspired by the geometrical modelling of vision, which has undergone a great development in the last ten years. There are, however, fundamental dissimilarities, due to the different role played by time and the different group of symmetries. The algorithm transforms the degraded sound in an ‘image’ in the time–frequency domain via a short-time Fourier transform. Such an image is then lifted to the Heisenberg group and is reconstructed via a Wilson–Cowan integro-differential equation. Preliminary numerical experiments are provided, showing the good reconstruction properties of the algorithm on synthetic sounds concentrated around two frequencies.https://doi.org/10.1186/s13408-020-00099-4 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ugo Boscain Dario Prandi Ludovic Sacchelli Giuseppina Turco |
spellingShingle |
Ugo Boscain Dario Prandi Ludovic Sacchelli Giuseppina Turco A bio-inspired geometric model for sound reconstruction Journal of Mathematical Neuroscience |
author_facet |
Ugo Boscain Dario Prandi Ludovic Sacchelli Giuseppina Turco |
author_sort |
Ugo Boscain |
title |
A bio-inspired geometric model for sound reconstruction |
title_short |
A bio-inspired geometric model for sound reconstruction |
title_full |
A bio-inspired geometric model for sound reconstruction |
title_fullStr |
A bio-inspired geometric model for sound reconstruction |
title_full_unstemmed |
A bio-inspired geometric model for sound reconstruction |
title_sort |
bio-inspired geometric model for sound reconstruction |
publisher |
SpringerOpen |
series |
Journal of Mathematical Neuroscience |
issn |
2190-8567 |
publishDate |
2021-01-01 |
description |
Abstract The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of this study is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is inspired by the geometrical modelling of vision, which has undergone a great development in the last ten years. There are, however, fundamental dissimilarities, due to the different role played by time and the different group of symmetries. The algorithm transforms the degraded sound in an ‘image’ in the time–frequency domain via a short-time Fourier transform. Such an image is then lifted to the Heisenberg group and is reconstructed via a Wilson–Cowan integro-differential equation. Preliminary numerical experiments are provided, showing the good reconstruction properties of the algorithm on synthetic sounds concentrated around two frequencies. |
url |
https://doi.org/10.1186/s13408-020-00099-4 |
work_keys_str_mv |
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