Methods demonstrate improved transition quality in music mixing using neural networks and generative models.
Methods for using artificial intelligence in automatic music mixing are considered. A system has been developed for automatically selecting transition points between tracks based on recurrent neural networks and dynamic time distortion algorithms. A method for improving the quality of transitions using generative adversarial networks for adaptive creation of effects is proposed. A mathematical model for analyzing audio features has been developed, including processing the tempo, tonality and dynamic characteristics of audio files.
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Lushkov et al. (2025) studied this question.
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