3D-DCDAE: Unsupervised Music Latent Representations Learning Method Based on a Deep 3D Convolutional Denoising Autoencoder for Music Genre Classification

3D-DCDAE: Unsupervised Music Latent Representations Learning Method Based on a Deep 3D Convolutional Denoising Autoencoder for Music Genre Classification

With unlabeled music data widely available, it is necessary to build an unsupervised latent music representation extractor to improve the performance of classification models. This paper proposes an unsupervised latent music representation learning method based on a deep 3D convolutional denoising a...

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Bibliographic Details
Main Authors: Lvyang Qiu, Shuyu Li, Yunsick Sung
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Mathematics
Subjects:
music genre classification
MIDI
autoencoder model
3D CNN
unsupervised learning
Online Access:https://www.mdpi.com/2227-7390/9/18/2274

Internet

https://www.mdpi.com/2227-7390/9/18/2274

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