## 4 Simulation Experiment and Result Analysis  
One male and one female speech signal from the TIMIT database randomly selected as the speech message to be sent, and the signal length is 3 s. The x-component of Chen chaotic system is chosen as the input chaotic signal, and the signal length of the intercepted x-component is the same as the length of speech signals, and the sampling frequency is \(f_{s}=16\) KHz. First, the speech signals are hidden into the chaotic signal to ensure the security of information transmission. Next, the impulse response filter is used to simulate the multipath effect generated by the speech transmission.  
It is important to note here that the filter length directly affects the degree of convolutional mixing of the source signal. The longer the filter, the longer the process of mixing response of the speech signal in the channel, and consequently the more complex the received observation signal and the more difficult the separation or extraction of the source speech signal. In order to simulate the actual transmission environment and for the signals safety, the filter length should be increased. Furthermore, taking into account the difficulty of the separation process, the filter length should be reduced to ensure that the Fast IVA algorithm can obtain better separation results. Considering the above, the filter length set in the experiment of this paper is \(p=20\).  
Then, the Fast IVA algorithm is used to separate and extract the speech signals from the observed signal, and the number of algorithm iterations is set to 1000 times. To ensure that the signal has good spectral characteristics in the frequency domain, the Hamming window function is chosen for the STFT transform, as in Section 2.2. Furthermore, the appropriate number of frequency points is \(K=512\), and the data frame is \(H=192\).  
Based on the above data and parameter selection, the simulation experiment is carried out and the selection of frequency points is considered in the experiment. The following is a quantitative analysis of the security of the speech signal, the separation results and separation performance of the Fast IVA algorithm, the evaluation of the speech quality, and the complexity of the algorithm from multiple perspectives.
The image information of the source signal and the observed signal after chaotic masking is shown in Figure 4. The time-domain waveform, spectrograms and histogram of the observed signal are given in Figure 4b-f, respectively, to compare the graphical information of the observed signal with that of the source signal. It is obvious that the source speech information is no longer found in the observed signal, which is enough to show that the chaotic signal plays a good masking effect on the speech signal and achieves the confidential transmission of speech information.  
Figure 4: The graphical information of the source and observed signals. (**a**) Time-domain waveform of the source signals; (**b**) Time-domain waveform of the observed signal. (**c**) Spectrogram of the source signal; (**d**) Spectrogram of the observed signal; (**e**) Histogram of the source signal; (**f**) Histogram of the observed signal.