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The use of multilayer perceptrons in isolated word recognition

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Book cover Artificial Neural Networks (IWANN 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 540))

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Abstract

Multilayer Perceptrons are the most widely used Artificial Neural Networks in Isolated Word Recognition. However, these networks do not adequately modelize the temporal structure of speech. In “static” classification of speech segments with Multilayer Perceptrons, the number of input nodes is fixed a priori, while the length of speech utterances is variable. In this paper, the technique called Trace Segmentation is explored in order to fit the lengths of both input layer and utterances. This technique has been studied both with the conventional Multilayer Perceptron with back propagation and with a combination of this algorithm and stochastic learning, as well as with other strategies such as Scaly Multilayer Perceptrons. Experimental results are reported, achieving performances that range from about 80% to nearly 100%, depending on the task (Spanish Digits and E-Set). These results are comparable to or higher than those obtained with Hidden Markov Models or more conventional and expensive Multilayer Perceptrons when applied to the same task.

On the other hand, the use of articulatory features has not been sufficiently explored in Isolated Word Recognition. In this paper we also deal with the problem of combining a module that exploits acoustic-articulatory relations with a conventional formalism such as a Multilayer Perceptron for an Isolated Word Recognition task as explained above. Some very preliminary experiments are presented under this framework.

This work has been partially supported by CICYT, under contract TIC-0048/89 and by ESPRIT (BRA) under contract 3279

Supported by a postgraduate grant from Conselleria Cultura, Educació i Ciència of Valencia.

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Authors and Affiliations

  1. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica Valencia, Spain

    M. J. Castro & F. Casacuberta

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  1. M. J. Castro
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  2. F. Casacuberta
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Alberto Prieto

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© 1991 Springer-Verlag Berlin Heidelberg

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Castro, M.J., Casacuberta, F. (1991). The use of multilayer perceptrons in isolated word recognition. In: Prieto, A. (eds) Artificial Neural Networks. IWANN 1991. Lecture Notes in Computer Science, vol 540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035913

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  • DOI: https://doi.org/10.1007/BFb0035913

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54537-8

  • Online ISBN: 978-3-540-38460-1

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