Optimized Neural Network Architecture for The Classification of Voice Signals
DOI:
https://doi.org/10.26438/ijcse/v6i9.502506Keywords:
Digital signal processing, Optimize neural network, Pattern classificationAbstract
In this paper, the performance to optimize feed-forward neural network has been evaluated for the classification of voice signals of English alphabets. There are various feed forward neural network models have been used earlier but the selection of optimize architecture is a challenge. In this paper we are implementing a optimize architecture which is best suitable for the classification of voice signals. Digital signal processing operations are applied on analog speech signals to convert them into digital form and then to make them suitable for further processing by neural network models.
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