Neuro-inspired speech recognition with recurrent spiking neurons

Arfan Ghani, T. M. McGinnity, Liam Maguire, Jim Harkin

Research output: Chapter in Book/Report/Conference proceedingChapter

18 Citations (Scopus)

Abstract

This paper investigates the potential of recurrent spiking neurons for classification problems. It presents a hybrid approach based on the paradigm of Reservoir Computing. The practical applications based on recurrent spiking neurons are limited due to their non-trivial learning algorithms. In the paradigm of Reservoir Computing, instead of training the whole recurrent network only the output layer (known as readout neurons) are trained. These recurrent neural networks are termed as microcircuits which are viewed as basic computational units in cortical computation. These microcircuits are connected as columns which are linked with other neighboring columns in cortical areas. These columns read out information from each other and can serve both as reservoir and readout. The design space for this paradigm is split into three domains; front end, reservoir, and back end. This work contributes to the identification of suitable front and back end processing techniques along with stable and compact reservoir dynamics, which provides a reliable framework for classification related problems.
Original languageEnglish
Title of host publicationNeuro-inspired speech recognition with recurrent spiking neurons
PublisherSpringer Verlag
Pages513-522
Number of pages10
ISBN (Electronic)978-3-540-87536-9
ISBN (Print)978-3-540-87535-2
DOIs
Publication statusPublished - 2008
Event18th International Conference on Artificial Neural Networks - Prague, Czech Republic
Duration: 3 Sep 20086 Sep 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume5163
ISSN (Print)0302-9743

Conference

Conference18th International Conference on Artificial Neural Networks
Abbreviated titleICANN 2008
CountryCzech Republic
CityPrague
Period3/09/086/09/08

Keywords

  • Reservoir computing
  • liquid state machine
  • hybrid neuro inspired computing
  • speech recognition

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  • Cite this

    Ghani, A., McGinnity, T. M., Maguire, L., & Harkin, J. (2008). Neuro-inspired speech recognition with recurrent spiking neurons. In Neuro-inspired speech recognition with recurrent spiking neurons (pp. 513-522). (Lecture Notes in Computer Science; Vol. 5163). Springer Verlag. https://doi.org/10.1007/978-3-540-87536-9_53