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Sound Recognition System Using Spiking and MLP Neural Networks

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Book cover Artificial Neural Networks and Machine Learning – ICANN 2016 (ICANN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9887))

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Abstract

In this paper, we explore the capabilities of a sound classification system that combines a Neuromorphic Auditory System for feature extraction and an artificial neural network for classification. Two models of neural network have been used: Multilayer Perceptron Neural Network and Spiking Neural Network. To compare their accuracies, both networks have been developed and trained to recognize pure tones in presence of white noise. The spiking neural network has been implemented in a FPGA device. The neuromorphic auditory system that is used in this work produces a form of representation that is analogous to the spike outputs of the biological cochlea. Both systems are able to distinguish the different sounds even in the presence of white noise. The recognition system based in a spiking neural networks has better accuracy, above 91 %, even when the sound has white noise with the same power.

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Acknowledgements

This work is supported by the Spanish government grant BIOSENSE (TEC2012-37868-C04-02) and by the excellence project from Andalusian Council MINERVA (P12-TIC-1300), both with support from the European Regional Development Fund.

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Authors and Affiliations

  1. Robotic and Technology of Computers Lab, Department of Architecture and Technology of Computers, University of Seville, Seville, Spain

    Elena Cerezuela-Escudero, Angel Jimenez-Fernandez, Rafael Paz-Vicente, Juan P. Dominguez-Morales, Manuel J. Dominguez-Morales & Alejandro Linares-Barranco

Authors
  1. Elena Cerezuela-Escudero
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  2. Angel Jimenez-Fernandez
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  3. Rafael Paz-Vicente
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  4. Juan P. Dominguez-Morales
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  5. Manuel J. Dominguez-Morales
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  6. Alejandro Linares-Barranco
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Correspondence to Elena Cerezuela-Escudero .

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Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

  2. University of Lausanne, Lausanne, Switzerland

    Paolo Masulli

  3. Universitat Politécnica de Catalunya, Terrrassa, Spain

    Antonio Javier Pons Rivero

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Cerezuela-Escudero, E., Jimenez-Fernandez, A., Paz-Vicente, R., Dominguez-Morales, J.P., Dominguez-Morales, M.J., Linares-Barranco, A. (2016). Sound Recognition System Using Spiking and MLP Neural Networks. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9887. Springer, Cham. https://doi.org/10.1007/978-3-319-44781-0_43

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  • DOI: https://doi.org/10.1007/978-3-319-44781-0_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44780-3

  • Online ISBN: 978-3-319-44781-0

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