Abstract: A neural-network-based disguised voices recognition model is proposed to realize the gender identification of the disguised speech speaker from the parameters such as the formant center frequency,bandwidth and intensity of sound.The model uses multi-layer perceptron(MLP) as the framework to obtain the gender recognition results through the fully connected non-linear stacking calculation,and uses L-BFGS to solve the parameters optimization in training.This paper uses SoundTouch to disguise the original voices of the male and the female respectively,and then linear predictive coding(LPC) extracts various parameters such as the center frequency,bandwidth and sound intensity of the formant,and eliminates the outliers.Then experiment is carried out to explore the influences of network structure and activation function on the model as well as the adaptability of this recognition model to different electronic disguised methods.The experimental results show that the MLP-based recognition model can effectively distinguish the gender of the speaker corresponding to the voice disguised by different methods.This laid the foundation for electronic disguised voice speaker recognition.

Key words: Multi-layer perceptron(MLP), Electronic disguised voice, Gender recognition, Formant, Speaker