A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions
S Ji, J Luo, X Yang - arXiv preprint arXiv:2011.06801, 2020 - arxiv.org
The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
A novel estimator of mutual information for learning to disentangle textual representations
Learning disentangled representations of textual data is essential for many natural language
tasks such as fair classification, style transfer and sentence generation, among others. The …
tasks such as fair classification, style transfer and sentence generation, among others. The …
CDPAM: Contrastive learning for perceptual audio similarity
Many speech processing methods based on deep learning require an automatic and
differentiable audio metric for the loss function. The DPAM approach of Manocha et al.[1] …
differentiable audio metric for the loss function. The DPAM approach of Manocha et al.[1] …
Music fadernets: Controllable music generation based on high-level features via low-level feature modelling
HH Tan, D Herremans - arXiv preprint arXiv:2007.15474, 2020 - arxiv.org
High-level musical qualities (such as emotion) are often abstract, subjective, and hard to
quantify. Given these difficulties, it is not easy to learn good feature representations with …
quantify. Given these difficulties, it is not easy to learn good feature representations with …
Learning disentangled representations of timbre and pitch for musical instrument sounds using gaussian mixture variational autoencoders
In this paper, we learn disentangled representations of timbre and pitch for musical
instrument sounds. We adapt a framework based on variational autoencoders with Gaussian …
instrument sounds. We adapt a framework based on variational autoencoders with Gaussian …
Musical composition style transfer via disentangled timbre representations
Music creation involves not only composing the different parts (eg, melody, chords) of a
musical work but also arranging/selecting the instruments to play the different parts. While …
musical work but also arranging/selecting the instruments to play the different parts. While …
Deep generative models for musical audio synthesis
M Huzaifah, L Wyse - Handbook of artificial intelligence for music …, 2021 - Springer
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MG-VAE: deep Chinese folk songs generation with specific regional styles
J Luo, X Yang, S Ji, J Li - Proceedings of the 7th Conference on Sound …, 2020 - Springer
Regional style in Chinese folk songs is a rich treasure that can be used for ethnic music
creation and folk culture research. In this paper, we propose MG-VAE, a music generative …
creation and folk culture research. In this paper, we propose MG-VAE, a music generative …
[PDF][PDF] Unsupervised Disentanglement of Pitch and Timbre for Isolated Musical Instrument Sounds.
Disentangling factors of variation aims to uncover latent variables that underlie the process
of data generation. In this paper, we propose a framework that achieves unsupervised pitch …
of data generation. In this paper, we propose a framework that achieves unsupervised pitch …
Anti-transfer learning for task invariance in convolutional neural networks for speech processing
We introduce the novel concept of anti-transfer learning for speech processing with
convolutional neural networks. While transfer learning assumes that the learning process for …
convolutional neural networks. While transfer learning assumes that the learning process for …