A random collection of recent works on music generation.
Papers
- Melody Generation for Pop Music via Word Representation of Musical Properties (2017.10) [arXiv] [Code]
- Generating Nontrivial Melodies for Music as a Service (2017.10) [arXiv] [Page]
- MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks (2017.9) [arXiv] [Page]
- Similarity Embedding Network for Unsupervised Sequential Pattern Learning by Playing Music Puzzle Games (2017.9)[arXiv] [Page]
- A Tutorial on Deep Learning for Music Information Retrieval (2017.9) [arXiv]
- Deep Learning Techniques for Music Generation - A Survey (2017.9) [arXiv] (论文综述)
- Neural Translation of Musical Style (2017.8) [arXiv] [Page]
- GLSR-VAE: Geodesic Latent Space Regularization for Variational AutoEncoder Architectures (2017.7) [arXiv]
- Learning and Evaluating Musical Features with Deep Autoencoders (2017.6) [arXiv]
- Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models (2017.5) [arXiv] [Code]
- MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions - ISMIR 2017 (2017.3) [arXiv] [Page]
- Automatic Conversion of Pop Music into Chiptunes for 8-bit Pixel Art - ICASSP 2017 (2017.2) [Paper] [Code] [Page]
- DeepBach: a Steerable Model for Bach Chorales Generation (2016.12) [arXiv] [Code]
- C-RNN-GAN: Continuous Recurrent Neural Networks with Adversarial Training (2016.11) [arXiv] [Code] 🌟
- Tuning Recurrent Neural Networks with Reinforcement Learning - ICLR 2017 (2016.11) [arXiv] [Web] [Code] 🌟
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient - AAAI 2017 (2016.9) [Paper] [Code]
- Song From PI: A Musically Plausible Network for Pop Music Generation - ICLR 2017 [arXiv] [Reports]🌟
- Text-based LSTM networks for Automatic Music Composition (2016.4) [arXiv] [Web] [Code]
- Music Transcription Modelling and Composition Using Deep Learning (2016.4) [arXiv] [Code]
- Composing A Melody with Long-short Term Memory (LSTM) Recurrent Neural Networks (2016.2) [Web] [Code] [Paper]
- Neural Adaptive Sequential Monte Carlo - NIPS 2015 (2015) [Paper]
- A Recurrent Latent Variable Model for Sequential Data - NIPS 2015 (2015) [Paper] [Code]
- AI Methods in Algorithmic Composition: A Comprehensive Survey (2013) [Paper] 🌟
- Modeling Temporal Dependencies in High-dimensional Sequences: Application to Polyphonic Music Generation and Transcription (2012) [arXiv]
- Towards Adaptive Music Generation By Reinforcement Learning of Musical Tension (2010) [Paper]
- A First Look at Music Composition using LSTM Recurrent Neural Networks (2002) [Web] [Paper]
Projects
- Google Magenta [Web] [Code]
- Deep Jazz [Web] [Code]
- BachBot [Web] [Code]
- WaveNet [Web][Code] (not fully)
- GRUV [Code]
- Kulitta [Code]
Applications
- AIVA[Link]
- Google A.I. Duet [Link]
- The Infinite Drum Machine [Link]
- Amper Music [Link]
- Intelligent Music System [Link]
- Unwind [Link]
- Tidalcycles [Link] [Video]
- Jukedeck [Link]
Conferences&Workshops
- ACM MM - ACM MultiMedia [Web]
- ISMIR - The International Society of Music Information Retrieval [Web]
- ICASSP - Conference on Acoustics, Speech and Signal Processing [Web]
- DLM - Deep Learning for Music Workshop [Web]
- CSMC - Conference on Computer Simulation of Musical Creativity [Web]
- CCRMA - Center for Computer Research in Music and Acoustics (Stanford University) [Web]
- ICMC - Internatonal Computer Music Conference [Web] [Lists]
Blogs
- Neural Nets for Generating Music [Web]
- Generative Music with JavaScript & Web Audio [Web]
- The Current State Of AI: Artificial Intelligence In Music, Movies & More (2017.7) [Web]
- Composing Music With Recurrent Neural Networks (2015.8) [Web] [Code]
- Analyzing deep learning tools for music generation [Web]
- COORD [Web]
- How evolved LSTMS improvise on a melogy you specify[Web]
- AI makes pop music in the style of any composer[Web]
- Richard Yang’s Blog[Blog]
- Thousands of bird sounds visualized using machine learning[Web]
- Music AI: Loop-in-the-Human[Web]