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Connectionist models for syllabic recognition in the time domain

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New Trends in Neural Computation (IWANN 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 686))

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Abstract

In this work we study the possibility of identifying syllables in the temporal domain of the speech signal using connectionist models. We set out a distributed neural network for the separated recognition of vowels and consonants. The network will act as a speech to text translator performing the recognition at the minimum level neccesary for its use as input to a semantic system. We have studied the features that the network shows when the input is a temporal-based or a frecuency-based signal.

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Author information

Authors and Affiliations

  1. Dept. Enxeñeria Industrial, Universidade da Coruña, E-15405, Ferrol (A Coruna), Spain

    J. Santos

  2. Dept. Computación, Facultade de Informática, Universidade da Coruña, E-15071, A Coruña, Spain

    R. P. Otero

Authors
  1. J. Santos
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  2. R. P. Otero
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José Mira Joan Cabestany Alberto Prieto

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© 1993 Springer-Verlag Berlin Heidelberg

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Santos, J., Otero, R.P. (1993). Connectionist models for syllabic recognition in the time domain. In: Mira, J., Cabestany, J., Prieto, A. (eds) New Trends in Neural Computation. IWANN 1993. Lecture Notes in Computer Science, vol 686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56798-4_139

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  • DOI: https://doi.org/10.1007/3-540-56798-4_139

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56798-1

  • Online ISBN: 978-3-540-47741-9

  • eBook Packages: Springer Book Archive

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