A Codec Simulation for Low-rate Speech Coding with Radial Neural Networks

A brief review of low-rate coding methods with the inclusion of neural networks in the codec structure is carried out. The issue of using radial neural networks for solving problems of low-speed coding and reducing the energy consumption of information transmission systems without communication quality degradation. The structure of a codec using radial neural networks in Matlab code is presented. Simulation of three-channel transmission system was performed for two signal type: human voice and music. Codec structure for each signal is the same, but neural network for music processing contains 69 neurons in hidden layer, while for voice 27 neurons is enough. The simulation shows that the application of a radial neural network as part of a predictive codec can reduce the dynamic range of signals by up to 70% while maintaining the communication quality for each of the used types of signal. At the same time, the simulation shows that codec with neural networks causes additional latency in signal processing.