## 4 Results and Discussion
### Importance of Acoustic Features for Different Feature Sets
For most music, the peaks of the spectrum roughly correspond to the harmonic components, whereas the valleys represent most of the non-harmonic components or noise. Consequently, spectral contrast can reflect the relative distribution of harmonic and non-harmonic components in the spectrum [40]. Spectral contrast is very important for the valence and arousal perception of Western classical music. It can be inferred that the contrast of peak and valley values of the music spectrum affects people's emotional judgement. The ratio of the harmonic component to the non-harmonic component plays an important role in emotion recognition of Western classical music, perhaps because Western musical instruments have more regular harmonics than Chinese instruments, making spectral contrast more significant for emotional perception of Western classical music. * HCDF is the harmony change detection function. The feature extraction method is shown in Figure 6. This feature represents the change in harmony between consecutive frames, and its essence is the flux of the tonal centroid [41]. HCDF is significant for both valence and arousal perception of Western and Chinese classical music, which indicates that HCDF is culturally universal. It can be concluded that the more frequent the harmony changes in music, the more obvious the changes in pleasure and activation perceived by people. * Onset Rate  
The onset rate represents the number of notes per second, which indirectly describes the tempo of music. In the algorithm, peak-picking is automatically performed on the onset detection curve to estimate the positions of the notes [42]. In both Western and Chinese classical music, the influence of onset rate on valence perception is stronger than that of arousal, which indicates that valence is highly related to the tempo of music. Figure 5: Flow diagram of spectral contrast. Figure 6: Flow diagram of the HCDF system. * Spectral Complexity Spectral complexity is a measure of the number of spectral peaks: the higher the number of spectral peaks, the higher the spectral complexity. [PERSON] et al. showed that relaxed music usually had lower spectral complexity, whereas non-relaxed music had higher spectral complexity [43]. Spectral complexity plays an important role in all scenarios, especially for the valence perception of Western classical music and the arousal perception of Chinese classical music, which indicates that the influence of spectral complexity on the emotional perception of Western and Chinese classical music is a somewhat different. * Spectral Flux Spectral flux is the difference in the spectrum amplitude between consecutive frames. This feature measures the rate of change in the spectrum structure and reflects the dynamic characteristics of the audio signal. Spectral flux is very important for the valence and arousal perception of Chinese classical music. Therefore, it is inferred that the greater the spectral flux, the more intense the spectral-domain energy of the music changes over time, and the higher the valence and arousal perception for Chinese classical music. Spectral flux is a culturally specific feature for Chinese classical music. * Dissonance Dissonance Dissonance is a timbre perceptual feature, and is also defined as roughness, based on a harmonic series of complex tones to study the influence of spectral features on sensory dissonance [44]. Dissonance is the most important feature for arousal perception of Chinese classical music. Because Chinese classical music emphasizes the personalization of musical instruments rather than the fusion [45], dissonance is an important aesthetic feature of Chinese classical music [46]. It can be concluded that dissonance is a culturally specific feature of Chinese classical music.