Neural networks for voiced/unvoiced speech classification

The results of designing, training, and testing a neural network for the voiced/unvoiced (V/UV) speech classification problem are described. A feedforward multilayer backpropagation network was used with six input, ten internal, and two output nodes-for a binary decision. The six features are common and easily computed. Training was done with 72 frames from two speakers. Testing was done with 479 frames from four speakers and resulted in a total of two errors (0.4%). Thus, a small neural network performs well on the V/UV problem