Speech Recognition Using Radial Basis Function Neural Network

Nurul Shairah, Hasna Merican (2010) Speech Recognition Using Radial Basis Function Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Speech recognition is the process of converting an acoustic signal, captured by a microphone or a telephone, to a set of words. The recognized words can be the final results, as for applications such as commands & control, data entry, and document preparation. They can also serve as the input to further linguistic processing in order to achieve speech understanding, a subject covered in section. In this paper, a speech recognition system using neural network (NN) with Radial Basis Function Neural Network (RBFNN) method is proposed. The training speed of RBFNN can be orders of magnitude faster [ 1] than the well known back propagation paradigm, and yet the ability of the network to generalize to detect the voice is approximately the same [2]. From this project, RBFNN method is to test the main and other voices. Then, show the output that and tell that the system can detect.

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