Device and method for extracting voiceprint feature of underwater acoustic target signal
A technology of target signal and voiceprint features, applied in speech analysis, instruments, etc., can solve problems such as limited representation ability of complex functions and restricted generalization ability.
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[0046] The used self-encoding deep neural network of the present invention is not less than three hidden layers, and the node number of each hidden layer is not less than 50, and concrete parameter setting is as shown in table 1, wherein 500 nodes are the frequency of original signal spectrum in the input layer Points, 51 nodes correspond to all frequencies within the value range of the fundamental frequency, and 5 nodes are 5-order harmonic orders from 3 to 7.
[0047] Table 1
[0048]
[0049] Using the above self-encoding deep neural network to extract the voiceprint feature of the underwater acoustic target signal, the obtained results are as follows: Figure 3 ~ Figure 5 shown, where image 3 and Figure 4 Shown is the reconstructed signal spectrum obtained by extracting the fundamental frequency and its harmonics of the target signal through the deep neural network, and reconstructing the original signal spectrum with noise generated by the simulation. imag...
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