In the current environment of folk music creation, it is found that the incubation rate of excellent music works is gradually decreasing. The introduction of electronic music technology provides a new possibility for the creation of folk music. Through electronic music technology, a new pattern of folk music creation can be established. This mode can not only break through the limitations of traditional creation mode but also greatly improve the efficiency and quality of creation. This paper constructs a folk music creation model based on electronic music technology and tests its functionality. First, choose a music studio as the laboratory, and then select electronic music technology built for audio acquisition and processing. Through integrated algorithms, different types of audio are placed into the system for unordered stacking and reassembly. Finally, the obtained audio combination is output to the audio output device to evaluate the results of the scheme, and the collected data are currently applied to the actual music fundamental frequency. In the evaluation stage, five types were selected and the results expressed in the plan were compared. To further improve the accuracy and reliability of authoring, we have also introduced integrated algorithms into this new authoring mode. By integrating the algorithm, the further creation and optimization of the music score can be realized, thus improving the accuracy and reliability of the creation. In the actual test, it is found that this mode of folk music creation based on electronic music technology is completely feasible. By testing the accuracy of music creation, it is found that this new creation mode can greatly improve the accuracy of music creation. In terms of the rationality of dealing with the complexity pattern of folk music design generation architecture, the music creation mode is significantly higher than the traditional processing mode. The processing of mixed design tasks is also more orderly than the response time of traditional state processing tasks. The overall effect of traditional methods can only reach 0.87, while the optimal effect of using information integration can reach 0.97.
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Jue Zhang (2024) studied this question.
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