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State of the Art of Music Generation with Deep Learning and AI
| Date | Stars |
|---|---|
| 2026-07-31 | 287 |
| 2026-08-04 | 287 |
| 2026-08-06 | 287 |
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# <span style="color:#9EB1FF; font-size:30.0pt">DEEP LEARNING FOR MUSIC GENERATION</span> This repository is maintained by [**Carlos Hernández-Oliván**](https://carlosholivan.github.io/index.html)([email protected]) and it presents the State of the Art of Music Generation. Most of these references (previous to 2022) are included in the review paper ["Music Composition with Deep Learning: A Review"](#https://arxiv.org/abs/2108.12290). The authors of the paper want to thank Jürgen Schmidhuber for his suggestions. [](./LICENSE) Make a pull request if you want to contribute to this references list. You can download a PDF version of this repo here: [README.pdf](AIMusicGeneration.pdf) All the images belong to their corresponding authors. ## Table of Contents 1. [Algorithmic Composition](#algorithmic-composition) - [1992](#1992alg) - [Books](#books-alg) 2. [Neural Network Architectures](#neural-network-architectures) 3. [Deep Learning Models for Symbolic Music Generation](#deep-learning-music-generation) - [2023](#2023deep) - [2022](#2022deep) - [2021](#2021deep) - [2020](#2020deep) - [2019](#2019deep) - [2018](#2018deep) - [2017](#2017deep) - [2016](#2016deep) - [2015](#2015deep) - [2002](#2002deep) - [1990s](#1990deep) - [Books and Reviews](#books-reviews-deep) - [Books](#books-deep) - [Reviews](#reviews-deep) 4. [Deep Learning Models for Audio Music Generation](#deep-learning-audio-generation) - [2023](#2023audiodeep) - [2022](#2022audiodeep) - [2021](#2021audiodeep) - [2020](#2020audiodeep) - [2017](#2017audiodeep) 5. [Datasets](#datasets) 6. [Journals and Conferences](#journals) 7. [Authors](#authors) 8. [Research Groups and Labs](#labs) 10. [Apps for Music Generation with AI](#apps) 11. [Other Resources](#other-resources) ## <span id="algorithmic-composition" style="color:#9EB1FF; font-size:25.0pt">2. Algorithmic Composition</span> ### <span id="1992alg" style="color:#A8FF9E; font-size:20.0pt">1992</span> #### <span id="harmonet" style="color:#FF9EC3; font-size:15.0pt">HARMONET</span> Hild, H., Feulner, J., & Menzel, W. (1992). HARMONET: A neural net for harmonizing chorales in the style of JS Bach. In Advances in neural information processing systems (pp. 267-274). [Paper](https://proceedings.neurips.cc/paper/1991/file/a7aeed74714116f3b292a982238f83d2-Paper.pdf) ### <span id="books-alg" style="color:#A8FF9E; font-size:25.0pt">Books</span> * Westergaard, P. (1959). Experimental Music. Composition with an Electronic Computer. * Todd, P. M. (1989). A connectionist approach to algorithmic composition. Computer Music Journal, 13(4), 27-43. * Cope, D. (2000). The algorithmic composer (Vol. 16). AR Editions, Inc.. * Nierhaus, G. (2009). Algorithmic composition: paradigms of automated music generation. Springer Science & Business Media. * Müller, M. (2015). Fundamentals of music processing: Audio, analysis, algorithms, applications. Springer. * McLean, A., & Dean, R. T. (Eds.). (2018). The Oxford handbook of algorithmic music. Oxford University Press. ## <span id="neural-network-architectures" style="color:#9EB1FF; font-size:25.0pt">2. Neural Network Architectures</span> | NN Architecture | Year | Authors | Link to original paper | Slides | | ------------- | ------------- | ------------- | ------------- | ------------- | | Long Short-Term Memory (LSTM) | 1997 | Sepp Hochreiter, Jürgen Schmidhuber | http://www.bioinf.jku.at/publications/older/2604.pdf | [LSTM.pdf](Slides/LSTM_v1.pdf) | | Convolutional Neural Network (CNN) | 1998 | Yann LeCun, Léon Bottou, YoshuaBengio, Patrick Haffner | http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf | | | Variational Auto Encoder (VAE) | 2013 | Diederik P. Kingma, Max Welling | https://arxiv.org/pdf/1312.6114.pdf | | Generative Adversarial Networks (GAN) | 2014 | Ian J. Goodfellow, Jean Pouget-A
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