Abstract
In recent years, due to the application of neural networks in music generation, a lot of music has appeared on the Internet, which poses more challenges for screening music and selecting songs. Although subjective evaluation is currently the ultimate choice for evaluating the beauty of songs, this method has limitations due to human resources and efficiency issues. Therefore, this paper combines information science and music science to propose an aesthetic computing framework for music composition on the Internet. Firstly, more accurate basic and advanced features of music are extracted by transcribing the separated musical accompaniment. Next, we will match them to the music rules. Then we use appropriate merging rules to determine the weight of elements, so as to achieve the purpose of calculating the aesthetic feeling of music composition. This paper presents for the first time a musical aesthetic evaluation framework combining music information dynamics, audio transcription and Zipf’wlaw. The experimental results prove that the objective beauty calculation method proposed is feasible and effective.
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Wang, S., Tie, Y., Li, X., Wang, X., Qi, L. (2023). Intelligence Evaluation of Music Composition Based on Music Knowledge. In: Huang, DS., Premaratne, P., Jin, B., Qu, B., Jo, KH., Hussain, A. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2023. Lecture Notes in Computer Science(), vol 14090. Springer, Singapore. https://doi.org/10.1007/978-981-99-4761-4_32
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DOI: https://doi.org/10.1007/978-981-99-4761-4_32
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