Structure of music feature disentanglement.

Structure of music feature disentanglement.

<div><p>Existing emotion-driven music generation models heavily rely on labeled data and lack interpretability and controllability of emotions. To address these limitations, a semi-supervised emotion-driven music generation model based on category-dispersed Gaussian mixture variational a...

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Bibliographic Details
Main Author: Zihao Ning (20485484) (author)
Other Authors: Xiao Han (102316) (author), Jie Pan (187977) (author)
Published: 2024
Subjects:
Neuroscience
Biological Sciences not elsewhere classified
world datasets demonstrate
objective loss function
distinct emotional clusters
driven music generation
model successfully disentangles
supervised model
tonal features
thereby strengthening
supervised emotion
latent space
latent representations
lack interpretability
labeled data
experimental results
emotion transitions
accurate emotion
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