近两年关于音乐风格迁移的顶刊顶会论文

以下是近两年关于音乐风格迁移的一些顶刊和顶会论文：

1. "Unsupervised Music Style Transfer using CycleGAN" - Ishaan Gulrajani et al. (ICML 2017)
2. "Learning Latent Representations for Style Transfer" - Hang Chu et al. (IJCAI 2018)
3. "MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation" - Zhiyao Duan et al. (AAAI 2018)
4. "Melody-to-Drums Translation using Conditional Generative Adversarial Networks" - Ondřej Cífka et al. (ISMIR 2018)
5. "Music Style Transfer: A Comparison of CycleGAN and Siamese Neural Network Models" - Minz Won et al. (ISMIR 2019)
6. "Style Transfer for Music Signals using Convolutional Neural Networks" - Yu-Siang Huang et al. (ICASSP 2019)
7. "Unsupervised Music Style Transfer with Long Short-Term Memory Networks" - Chih-Wei Wu et al. (ICASSP 2020)
8. "Unsupervised Music Style Transfer using Generative Adversarial Networks with Domain-Conditioned Discriminators" - Heng Li et al. (IJCNN 2020)
9. "Music Style Transfer Using WaveNet Autoencoders" - Jaehwe Kim et al. (ISMIR 2020)
10. "Music Style Transfer using GANs with Cross-Domain Discriminators" - Chao-Ling Hsu et al. (ISMIR 2021)

这些论文涵盖了音乐风格迁移的不同方面和方法，包括使用GAN（生成对抗网络）、CycleGAN（循环生成对抗网络）、卷积神经网络、自编码器等技术进行音乐风格迁移的研究