Analyzing AI composition techniques and their influence on human musical aesthetics using bi-GRU and self-attention models
Vol 9, Issue 11, 2024, Article identifier:
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Abstract
With the continuous development of artificial intelligence technology, this study aims to explore the application of artificial intelligence in human aesthetics. By processing the signal in sub frames and using short-time Fourier transform to analyze the position information of beat points, the start and key musical features of notes can be accurately detected. Based on the extracted music features, a Bi GRU network and self-attention mechanism automatic composition model are established to process important information between longer sequence predictions and prominent notes, and to evaluate the accuracy and vividness of AI composed music works. The results showed that the model achieved an accuracy of 94.28% in processing melody and rhythm data. Excellent performance in terms of music fluency and coordination, with high scores in human music aesthetics indicators, reaching a pitch score of 92, and classical style scores of 90 and 92 in melody and integrity. Artificial intelligence has to some extent influenced and shaped human music aesthetics, providing important evidence for understanding its impact on music creation.
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DOI: https://doi.org/10.59429/esp.v9i11.3081
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Copyright (c) 2024 Qi Gao,Jinting Cai, Fuxin Wang, Junsong Chang, He Huang
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