Abstract
The use of Recurrent Neutral Networks is not so widely extended as Feedforward Neutral Networks. In recent years, these neutral networks are being very studied and they are giving better results than feedforward neural networks in problems related on control, pattern recognition, etc.
In this paper, we present a neural model for speech recognition, whose main characteristic is the little number of neurons that uses and the good results that obtains.
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References
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© 2001 Springer-Verlag Berlin Heidelberg
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Blanco, A., Delgado, M., Pegalajar, M.C., Requena, I. (2001). Speech Recognition Using Fuzzy Second-Order Recurrent Neural Networks. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_32
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DOI: https://doi.org/10.1007/3-540-45720-8_32
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