Analysis of the influence of selected audio pre-processing stages on accuracy of speaker language recognition

Abstract

In the course of the work, the best sequence of stages of pre-processing audio data was selected for use in further training of the neural network for different ways to convert signals into features. Mel-cepstral characteristic coefficients are better suited for solving our problem. Since the neural network strongly depends on its structure, the results may change with the increase in the volume of input data and the number of languages. But at this stage, it was decided to use only mel-cepstral characteristic coefficients with normalization.