“Speak, Read and Prompt (SPEAR-TTS): High-Fidelity Text-to-Speech With Minimal Supervision”, Kharitonov Et Al 2023

“Speak, Read and Prompt (SPEAR-TTS): High-Fidelity Text-to-Speech with Minimal Supervision”⁠, Eugene Kharitonov, Damien Vincent, Zalán Borsos, Raphaël Marinier, Sertan Girgin, Olivier Pietquin, Matt Sharifi2023-02-07 (T5 Transformer; similar)

“Archisound: Audio Generation With Diffusion”, Schneider2023

“Archisound: Audio Generation With Diffusion”⁠, Flavio Schneider2023-01-16 (diffusion model; similar; bibliography)

“Msanii: High Fidelity Music Synthesis on a Shoestring Budget”, Maina2023

“Msanii: High Fidelity Music Synthesis on a Shoestring Budget”⁠, Kinyugo Maina2023-01-16 (diffusion model; similar)

“Rock Guitar Tablature Generation via Natural Language Processing”, Casco-Rodriguez2023

“Rock Guitar Tablature Generation via Natural Language Processing”⁠, Josue Casco-Rodriguez2023-01-12 (GPT; similar)

“VALL-E: Neural Codec Language Models Are Zero-Shot Text to Speech Synthesizers”, Wang Et Al 2023

“VALL-E: Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers”⁠, Chengyi Wang, Sanyuan Chen, Yu Wu, Ziqiang Zhang, Long Zhou, Shujie Liu, Zhuo Chen, Yanqing Liu, Huaming Wang2023-01-05 (DALL·E⁠, AI scaling; similar; bibliography)

“High Fidelity Neural Audio Compression”, Défossez Et Al 2022

“High Fidelity Neural Audio Compression”⁠, Alexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi2022-10-24 (GAN; similar; bibliography)

“Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Takahashi Et Al 2022

“Hierarchical Diffusion Models for Singing Voice Neural Vocoder”⁠, Naoya Takahashi, Mayank Kumar, Singh, Yuki Mitsufuji2022-10-14 (diffusion model; similar; bibliography)

“RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”, Anonymous2022

“RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”⁠, Anonymous2022-09-29 (diffusion model; similar)

“AudioLM: a Language Modeling Approach to Audio Generation”, Borsos Et Al 2022

“AudioLM: a Language Modeling Approach to Audio Generation”⁠, Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matt Sharifi, Olivier Teboul2022-09-07 (LM tokenization⁠, Jukebox; similar)

“MeloForm: Generating Melody With Musical Form Based on Expert Systems and Neural Networks”, Lu Et Al 2022

“MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks”⁠, Peiling Lu, Xu Tan, Botao Yu, Tao Qin, Sheng Zhao, Tie-Yan Liu2022-08-30 (Transformer NN; similar)

“AI Composer Bias: Listeners like Music Less When They Think It Was Composed by an AI”, Shank Et Al 2022

“AI composer bias: Listeners like music less when they think it was composed by an AI”⁠, Daniel B. Shank, Courtney Stefanik, Cassidy Stuhlsatz, Kaelyn Kacirek, Amy M. Belfi2022-08-25 (culture; similar; bibliography)

“Musika! Fast Infinite Waveform Music Generation”, Pasini & Schlüter2022

“Musika! Fast Infinite Waveform Music Generation”⁠, Marco Pasini, Jan Schlüter2022-08-18 (GAN; similar)

“Multitrack Music Transformer: Learning Long-Term Dependencies in Music With Diverse Instruments”, Dong Et Al 2022

“Multitrack Music Transformer: Learning Long-Term Dependencies in Music with Diverse Instruments”⁠, Hao-Wen Dong, Ke Chen, Shlomo Dubnov, Julian McAuley, Taylor Berg-Kirkpatrick2022-07-14 (self-attention; similar)

“CLAP: Learning Audio Concepts From Natural Language Supervision”, Elizalde Et Al 2022

“CLAP: Learning Audio Concepts From Natural Language Supervision”⁠, Benjamin Elizalde, Soham Deshmukh, Mahmoud Al Ismail, Huaming Wang2022-06-09 (CLIP; similar)

“BigVGAN: A Universal Neural Vocoder With Large-Scale Training”, Lee Et Al 2022

“BigVGAN: A Universal Neural Vocoder with Large-Scale Training”⁠, Sang-gil Lee, Wei Ping, Boris Ginsburg, Bryan Catanzaro, Sungroh Yoon2022-06-09 (CNN⁠, GAN/data-augmentation⁠, StyleGAN⁠, AI scaling; similar; bibliography)

“Tradformer: A Transformer Model of Traditional Music Transcriptions”, Casini & Sturm2022

“Tradformer: A Transformer Model of Traditional Music Transcriptions”⁠, Luca Casini, Bob Sturm2022-05-20 (Transformer NN; similar)

“SymphonyNet: Symphony Generation With Permutation Invariant Language Model”, Liu Et Al 2022

“SymphonyNet: Symphony Generation with Permutation Invariant Language Model”⁠, Jiafeng Liu, Yuanliang Dong, Zehua Cheng, Xinran Zhang, Xiaobing Li, Feng Yu, Maosong Sun2022-05-10 (ML dataset⁠, LM tokenization⁠, Transformer NN; similar)

“It’s Raw! Audio Generation With State-Space Models”, Goel Et Al 2022

“It’s Raw! Audio Generation with State-Space Models”⁠, Karan Goel, Albert Gu, Chris Donahue, Christopher Ré2022-02-20 (self-attention; backlinks; similar; bibliography)

“General-purpose, Long-context Autoregressive Modeling With Perceiver AR”, Hawthorne Et Al 2022

“General-purpose, long-context autoregressive modeling with Perceiver AR”⁠, Curtis Hawthorne, Andrew Jaegle, Cătălina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski2022-02-15 (RNN⁠, self-attention⁠, video generation; similar; bibliography)

“FIGARO: Generating Symbolic Music With Fine-Grained Artistic Control”, Rütte Et Al 2022

“FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control”⁠, Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hoffman2022-01-26 (NN sampling⁠, Transformer NN; similar)

“Steerable Discovery of Neural Audio Effects”, Steinmetz & Reiss2021

“Steerable discovery of neural audio effects”⁠, Christian J. Steinmetz, Joshua D. Reiss2021-12-06 (similar)

“Semi-Supervised Music Tagging Transformer”, Won Et Al 2021

“Semi-Supervised Music Tagging Transformer”⁠, Minz Won, Keunwoo Choi, Xavier Serra2021-11-26 (Transformer NN; similar)

“AudioCLIP: Extending CLIP to Image, Text and Audio”, Guzhov Et Al 2021

“AudioCLIP: Extending CLIP to Image, Text and Audio”⁠, Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel2021-06-24 (CLIP; backlinks; similar; bibliography)

“MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis”, Tae Et Al 2021

“MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis”⁠, Jaesung Tae, Hyeongju Kim, Younggun Lee2021-06-15 (MLP NN⁠, GAN; backlinks; similar)

“PriorGrad: Improving Conditional Denoising Diffusion Models With Data-Dependent Adaptive Prior”, Lee Et Al 2021

“PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior”⁠, Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon2021-06-11 (diffusion model; similar)

“DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”, Liu Et Al 2021

“DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”⁠, Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, Zhou Zhao2021-05-06 (diffusion model; similar)

“Symbolic Music Generation With Diffusion Models”, Mittal Et Al 2021

“Symbolic Music Generation with Diffusion Models”⁠, Gautam Mittal, Jesse Engel, Curtis Hawthorne, Ian Simon2021-03-30 (diffusion model/discrete⁠, autoencoder NN; similar)

“Interacting With GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation”, Geerlings & Meroño-Peñuela2020

“Interacting with GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation”⁠, Cariña Geerlings, Albert Meroño-Peñuela2020-10-16 (NN sampling⁠, GPT; backlinks; similar)

“HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis”, Kong Et Al 2020

“HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis”⁠, Jungil Kong, Jaehyeon Kim, Jaekyoung Bae2020-10-12 (GAN; similar)

“AI Song Contest: Human-AI Co-Creation in Songwriting”, Huang Et Al 2020

“AI Song Contest: Human-AI Co-Creation in Songwriting”⁠, Cheng-Zhi Anna Huang, Hendrik Vincent Koops, Ed Newton-Rex, Monica Dinculescu, Carrie J. Cai2020-10-12 (similar)

“DeepSinger: Singing Voice Synthesis With Data Mined From the Web”, Ren Et Al 2020

“DeepSinger: Singing Voice Synthesis with Data Mined From the Web”⁠, Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu2020-07-09 (RNN⁠, Transformer NN; similar)

“Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models”, Papadimitriou & Jurafsky2020

“Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models”⁠, Isabel Papadimitriou, Dan Jurafsky2020-04-30 (RNN; similar)

“15.ai”, 15 & Project2020

“15.ai”⁠, 15, Pony Preservation Project2020-03-06 (backlinks; similar; bibliography)

“Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions”, Huang & Yang2020

“Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions”⁠, Yu-Siang Huang, Yi-Hsuan Yang2020-02-01 (GPT; backlinks; similar)

“Writing the Next American Hit: Using GPT-2 to Explore the Possibility of Creating Successful AI-Generated Song Lyrics Possibility of Creating Successful AI-Generated Song Lyric”, Barrio2020

“GPT-2 Preference Learning for Music Generation”, Branwen2019

“GPT-2 Preference Learning for Music Generation”⁠, Gwern Branwen2019-12-16 (GPT fiction⁠, GPT poetry⁠, shell⁠, order statistics/comparison⁠, tutorial; backlinks; similar; bibliography)

“Encoding Musical Style With Transformer Autoencoders”, Choi Et Al 2019

“Encoding Musical Style with Transformer Autoencoders”⁠, Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel2019-12-10 (Transformer NN⁠, autoencoder NN; backlinks; similar)

“GPT-2 Folk Music”, Branwen & Presser2019

“GPT-2 Folk Music”⁠, Gwern Branwen, Shawn Presser2019-11-01 (GPT⁠, shell⁠, statistics; backlinks; similar; bibliography)

“Parallel WaveGAN: A Fast Waveform Generation Model Based on Generative Adversarial Networks With Multi-resolution Spectrogram”, Yamamoto Et Al 2019

“Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram”⁠, Ryuichi Yamamoto, Eunwoo Song, Jae-Min Kim2019-10-25 (GAN; similar)

“Low-dimensional Embodied Semantics for Music and Language”, Raposo Et Al 2019

“Low-dimensional Embodied Semantics for Music and Language”⁠, Francisco Afonso Raposo, David Martins de Matos, Ricardo Ribeiro2019-06-20 (RL/brain-imitation-learning; similar)

“MuseNet: a Deep Neural Network That Can Generate 4-minute Musical Compositions With 10 Different Instruments, and Can Combine Styles from Country to Mozart to the Beatles”, Payne2019

“MuseNet: a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles”⁠, Christine Payne2019-04-25 (GPT; backlinks; similar; bibliography)

“Generative Modeling With Sparse Transformers: We’ve Developed the Sparse Transformer, a Deep Neural Network Which Sets New Records at Predicting What Comes next in a Sequence—whether Text, Images, or Sound. It Uses an Algorithmic Improvement of The Attention Mechanism to Extract Patterns from Sequences 30× Longer Than Possible Previously”, Child & Gray2019

“Generative Modeling with Sparse Transformers: We’ve developed the Sparse Transformer, a deep neural network which sets new records at predicting what comes next in a sequence—whether text, images, or sound. It uses an algorithmic improvement of the attention mechanism to extract patterns from sequences 30× longer than possible previously”⁠, Rewon Child, Scott Gray2019-04-23 (sparse Transformer⁠, GPT; backlinks; similar)

“Music Transformer: Generating Music With Long-Term Structure”, Huang Et Al 2018

“Music Transformer: Generating Music with Long-Term Structure”⁠, Cheng-Zhi Anna Huang, Ian Simon, Monica Dinculescu2018-12-13 (GPT; backlinks; similar; bibliography)

“Piano Genie”, Donahue Et Al 2018

“Piano Genie”⁠, Chris Donahue, Ian Simon, Sander Dieleman2018-10-11 (RNN⁠, autoencoder NN; similar)

“Music Transformer”, Huang Et Al 2018

“Music Transformer”⁠, Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Ian Simon, Curtis Hawthorne, Andrew M. Dai2018-09-12 (self-attention; similar)

“This Time With Feeling: Learning Expressive Musical Performance”, Oore Et Al 2018

“This Time with Feeling: Learning Expressive Musical Performance”⁠, Sageev Oore, Ian Simon, Sander Dieleman, Douglas Eck, Karen Simonyan2018-08-10 (RNN; similar)

“The Challenge of Realistic Music Generation: Modelling Raw Audio at Scale”, Dieleman Et Al 2018

“The challenge of realistic music generation: modelling raw audio at scale”⁠, Sander Dieleman, Aäron van den Oord, Karen Simonyan2018-06-26 (autoencoder NN; similar)

“The Sound of Pixels”, Zhao Et Al 2018

“The Sound of Pixels”⁠, Hang Zhao, Chuang Gan, Andrew Rouditchenko, Carl Vondrick, Josh McDermott, Antonio Torralba2018-04-09 (ML dataset⁠, video analysis; similar)

“Efficient Neural Audio Synthesis”, Kalchbrenner Et Al 2018

“Efficient Neural Audio Synthesis”⁠, Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg2018-02-23 (RNN⁠, NN pruning; similar)

“Generating Structured Music through Self-Attention”, Huang Et Al 2018

“Generating Structured Music through Self-Attention”⁠, Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Andrew Dai, Matt Hoffman, Curtis Hawthorne2018 (Transformer NN; similar; bibliography)

“Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Raposo Et Al 2017

“Towards Deep Modeling of Music Semantics using EEG Regularizers”⁠, Francisco Raposo, David Martins de Matos, Ricardo Ribeiro, Suhua Tang, Yi Yu2017-12-14 (retrieval AI⁠, RL/brain-imitation-learning; similar)

“Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models”, Guimaraes Et Al 2017

“Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models”⁠, Gabriel Lima Guimaraes, Benjamin Sanchez-Lengeling, Carlos Outeiral, Pedro Luis Cunha Farias, Alán Aspuru-Guzik2017-05-30 (GAN⁠, model-free RL; backlinks; similar)

“Neural Audio Synthesis of Musical Notes With WaveNet Autoencoders”, Engel Et Al 2017

“Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders”⁠, Jesse Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Douglas Eck, Karen Simonyan, Mohammad Norouzi2017-04-05 (autoencoder NN; similar)

“Tuning Recurrent Neural Networks With Reinforcement Learning”, Jaques Et Al 2017

“Tuning Recurrent Neural Networks with Reinforcement Learning”⁠, Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck2017-02-14 (RNN⁠, NN sampling⁠, model-free RL; backlinks; similar)

“SampleRNN: An Unconditional End-to-End Neural Audio Generation Model”, Mehri Et Al 2016

“SampleRNN: An Unconditional End-to-End Neural Audio Generation Model”⁠, Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron Courville2016-12-22 (RNN; backlinks; similar)

“WaveNet: A Generative Model for Raw Audio”, Oord Et Al 2016

“WaveNet: A Generative Model for Raw Audio”⁠, Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner2016-09-12 (NN sampling; similar)

“The Abc Music Standard 2.1: §3.1.1: X: - Reference Number”, Walshaw2011

“The abc music standard 2.1: §3.1.1: X: - reference number”⁠, Chris Walshaw2011-12 (similar)

“Connectionist Music Composition Based on Melodic, Stylistic, and Psychophysical Constraints [Technical Report CU-CS–495–90]”, Mozer1990

“Connectionist Music Composition Based on Melodic, Stylistic, and Psychophysical Constraints [Technical report CU-CS–495–90]”⁠, Michael C. Mozer1990 (RNN; backlinks; similar)

Wikipedia

1. DarwinTunes