## 4 Experiment
### Subjective Evaluation  
In the evaluation experiment, we focused more on the subjective evaluation of users. Among several subjective evaluation methodologies, the consensual assessment technique (CAT) was the most suitable method in this case. The CAT method is also called the \"Gold Standard\" of creativity assessment and is one of the most effective tools for measuring creative works, such as arts, engineering as well as business management. It can evaluate  
Figure 4: The connection of visual and audio. our results because our creations were open, novel and appropriate. Firstly, we organized the people familiar with the field of music composition to form an evaluation team. Our team consisted of five professors of music-related major at the Communication University of China and seven musicians who had published music pieces on the Internet and had a certain popularity. Secondly, we told the audiences what aspects of the work they needed to evaluate. We chose the following metrics as evaluation standards:  
1. Rhythm represents how the rhythm of the music fits into the pace of movement in the given video;
2. Emotional foil indicates whether the emotional expression of music is suitable for the content of the video;
3. Highlight says whether the music is stressed in key parts of the video;
4. Structure indicates whether the music is suitable for the background music with a crescendo at the beginning and a weakening at the end of the video. Finally, the evaluator evaluated all independent evaluation of the heard music pieces. Inspired by [1], the music pieces of five scenes were chosen, with three pieces of music for each. The selected five scenes were as follows: night scene, animals in the desert of snow mountains, battlefield, animated movie of animals and animated movie of characters. Furthermore, each piece was clipped to thirty seconds to keep the same experiment conditions. We used the Likert scale five-point method to divide the evaluation opinion into five grades, with a score ranging from one to five. In addition, considering the evaluation of music has a great relationship with subjective feelings and the feelings vary from person to person, we also chose 23 students without music knowledge background at the Communication University of China to make up our second evaluation group, and they also made independent evaluation of the same aspects. As the CAT technique is based on the evaluators' perception of implicit theories of creativity, the subjectivity is relatively high. As a result, we calculated the raters' Cronbach score to reflect the reliability of the evaluation method after collecting the scores. From Figure 5, we find that most of the Cronbach scores of the expert group was higher than 0.7, which means the results can be accepted. In addition, we also calculated the statistics of the voting distribution for the two groups of evaluators, which is shown in Figure 6. One interesting finding is that the expert group voted less for a score of three than the other group, and they were also less likely to give a score of five. Figure 5: The Cronbach score of voting scores of the expert evaluation group. Then, we observed the scores on each evaluation index. Table 1 shows the average rating results of the expert group of the five scenes fit to the music generated by the algorithm, compared to the music made by the composer, calculated by Formula (6). \(N=12\) represents the number of people of the expert group. \[Vij=\frac{\sum_{n=1}^{n=N}\left(S_{jm1}+S_{jm2}+S_{jm3}\right)}{N}, \tag{6}\]  
The values in Table 1 represent the expert group's score of this aspect of the generated music for each scene, and that in brackets represents the score of the music made by the composer.