Mandarin tone recognition by multi-layer perceptron

Tone recognition of isolated Mandarin monosyllables using the multilayer perceptron (MLP) model is reported. Ten features extracted from the fundamental frequency and energy contours of a monosyllable are used as the recognition features. The backpropagation algorithm is used to train the internal representation of the MLP. Several variations of the MLP with regard to the number of layers and the number of neurons in each layer are considered. In a speaker-untrained test, a recognition rate of 93.8% was achieved. It outperforms a Gaussian classifier which has a recognition rate of 90.6%