## 6 Experiment
### Experimental Results and Analysis  
#### 6.6.1 Analysis of the IMel Spectrogram  
(1) Factors influencing the spectrogram  
How to get the most suitable spectrogram is the implementation challenge, because in the process of spectrogram implementation, the FFT length is 256, the window length is 256, the window shift is 128, and many other parameters have an impact on the results, such as the number M of filters and the frequency range R.  
The number M of filters in the filter bank has an important influence on the display of the spectrogram. Figure 9a shows the filter banks with 20 filters, Figure 9b shows the Mel spectrogram corresponding to Figure 9a,c shows a filter bank with 40 filters, and Figure 9d shows the Mel spectrogram corresponding to Figure 9c. It can be observed that the spectrogram of Figure 9d is more detailed and obvious than that of Figure 9b, and is therefore more suitable for emotion detection.  
The vertical axis of the spectrogram indicates frequency and the horizontal axis indicates time. In this paper, \(R\) represents the frequency range of the spectrogram and \(R_{\text{max}}\) represents the maximum frequency. Both \(R\) and \(R_{\text{max}}\) have an important impact on recognition. According to the Nyquist principle, the maximum frequency \(f_{m}\) is equal to  
Figure 9: (**a**) Mel filter banks M = 20. (**b**) Mel spectrogram M = 20. (**c**) Mel filter banks M = 40. (**d**) Mel.spectrogram M = 40.  
half of the sampling frequency \(f_{s}\). For example, the sampling frequency of the SAVEE dataset is 44,200 Hz and the maximum frequency is 22,100 Hz. As shown in Figure 10a,c, the frequency ranges of the Mel filter banks and IMel filter banks are 0-4000 Hz, and Figure 10b,d show the corresponding Mel spectrogram and IMel spectrogram. In Figure 10e,g, the frequency ranges of the Mel filter and IMel filter are both 0-8000 Hz, and Figure 10f,h show the corresponding Mel spectrogram and IMel spectrogram. In Figure 10i,k, the frequency ranges of the Mel filter and IMel filter are both 0-21,000 Hz, and Figure 10j,l show the corresponding Mel spectrogram and IMel spectrogram. It can be observed that the low-frequency decomposition of the Mel spectrogram in Figure 10j is not sufficiently detailed, whereas the attention in Figure 10l is mostly in the invalid region. Therefore, the following work later section of this paper is to set the frequency range at 0-4000 Hz or 0-8000 Hz.  
(2) Complementarity analysis of Mel spectrogram and IMel spectrogram  
To prove that the Mel spectrogram and IMel spectrogram are complementary, the correlation analysis method is used in this paper. For two related variables, the correlation coefficient (whose value is between \(-\)1 and 1) indicates the degree of correlation. A greater absolute value of the correlation coefficient indicates more obvious emotional information and a brighter reflection in the image. As shown in Figure 11a-c, a correlation analysis of Mel deep features, IMel deep features, and Mel + IMel deep features of 480 sentences in the SAVEE database was conducted and expressed in the form of images. The abscissa and ordinate represent the 480 samples, The color of anger is bright in Figure 11a, dark in Figure 11b, and brighter in Figure 11c. The color of sadness is dark in Figure 11a, bright in Figure 11b, and brighter in Figure 11c. This shows that the Mel deep features and the IMel deep features are complementary, Moreover, the Mel + IMel deep features can maintain the advantage of each of them and can enhance the overall advantage, thereby playing a role in enhancing emotional information.