Towards spike-based speech processing: A biologically plausible approach to simple acoustic classification

Ismail Uysal; Harsha Sathyendra; John G. Harris

International Journal of Applied Mathematics and Computer Science (2008)

  • Volume: 18, Issue: 2, page 129-137
  • ISSN: 1641-876X

Abstract

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Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology seeking clues to make better engineered systems, and ASR is no exception with the usage of feature sets such as Mel frequency cepstral coefficients, which employ filter banks similar to cochlear filter banks in frequency distribution and bandwidth. In this paper, we delve deeper into the mechanics of the human auditory system to take this biological inspiration to the next level. The main goal of this research is to investigate the computation potential of spike trains produced at the early stages of the auditory system for a simple acoustic classification task. First, various spike coding schemes from temporal to rate coding are explored, together with various spike-based encoders with various simplicity levels such as rank order coding and liquid state machine. Based on these findings, a biologically plausible system architecture is proposed for the recognition of phonetically simple acoustic signals which makes exclusive use of spikes for computation. The performance tests show superior performance on a noisy vowel data set when compared with a conventional ASR system.

How to cite

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Ismail Uysal, Harsha Sathyendra, and John G. Harris. "Towards spike-based speech processing: A biologically plausible approach to simple acoustic classification." International Journal of Applied Mathematics and Computer Science 18.2 (2008): 129-137. <http://eudml.org/doc/207871>.

@article{IsmailUysal2008,
abstract = {Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology seeking clues to make better engineered systems, and ASR is no exception with the usage of feature sets such as Mel frequency cepstral coefficients, which employ filter banks similar to cochlear filter banks in frequency distribution and bandwidth. In this paper, we delve deeper into the mechanics of the human auditory system to take this biological inspiration to the next level. The main goal of this research is to investigate the computation potential of spike trains produced at the early stages of the auditory system for a simple acoustic classification task. First, various spike coding schemes from temporal to rate coding are explored, together with various spike-based encoders with various simplicity levels such as rank order coding and liquid state machine. Based on these findings, a biologically plausible system architecture is proposed for the recognition of phonetically simple acoustic signals which makes exclusive use of spikes for computation. The performance tests show superior performance on a noisy vowel data set when compared with a conventional ASR system.},
author = {Ismail Uysal, Harsha Sathyendra, John G. Harris},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {spike coding; synchrony coding; phase locking; speech perception; psychoacoustics; speech recognition},
language = {eng},
number = {2},
pages = {129-137},
title = {Towards spike-based speech processing: A biologically plausible approach to simple acoustic classification},
url = {http://eudml.org/doc/207871},
volume = {18},
year = {2008},
}

TY - JOUR
AU - Ismail Uysal
AU - Harsha Sathyendra
AU - John G. Harris
TI - Towards spike-based speech processing: A biologically plausible approach to simple acoustic classification
JO - International Journal of Applied Mathematics and Computer Science
PY - 2008
VL - 18
IS - 2
SP - 129
EP - 137
AB - Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology seeking clues to make better engineered systems, and ASR is no exception with the usage of feature sets such as Mel frequency cepstral coefficients, which employ filter banks similar to cochlear filter banks in frequency distribution and bandwidth. In this paper, we delve deeper into the mechanics of the human auditory system to take this biological inspiration to the next level. The main goal of this research is to investigate the computation potential of spike trains produced at the early stages of the auditory system for a simple acoustic classification task. First, various spike coding schemes from temporal to rate coding are explored, together with various spike-based encoders with various simplicity levels such as rank order coding and liquid state machine. Based on these findings, a biologically plausible system architecture is proposed for the recognition of phonetically simple acoustic signals which makes exclusive use of spikes for computation. The performance tests show superior performance on a noisy vowel data set when compared with a conventional ASR system.
LA - eng
KW - spike coding; synchrony coding; phase locking; speech perception; psychoacoustics; speech recognition
UR - http://eudml.org/doc/207871
ER -

References

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