Fetching the paper…
Reading the bibliography…
In this paper we propose a novel generative approach, DiffRoll, to tackle automatic music transcription (AMT).
“Non-negative matrix factorization for polyphonic music transcription,”
Paris Smaragdis and Judith C Brown, · 2003
Earlier work this paper cites.
Bayesian music transcription
Ali Taylan Cemgil, · 2004
Earlier work this paper cites.
“Maps-a piano database for multipitch estimation and automatic transcription of music,”
Valentin Emiya, Nancy Bertin, Bertrand David, and Roland Badeau, · 2010
Earlier work this paper cites.
“A classification-based polyphonic piano transcription approach using learned feature representations.,”
Juhan Nam, Jiquan Ngiam, Honglak Lee, Malcolm Slaney, et al., · 2011
Earlier work this paper cites.
“Unsupervised transcription of piano music,”
Taylor Berg-Kirkpatrick, Jacob Andreas, and Dan Klein, · 2014
Earlier work this paper cites.
“Deep unsupervised learning using nonequilibrium thermodynamics,”
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli, · 2015
Earlier work this paper cites.
“An end-to-end neural network for polyphonic piano music transcription,”
Siddharth Sigtia, Emmanouil Benetos, and Simon Dixon, · 2015
Earlier work this paper cites.
“Onsets and frames: Dual-objective piano transcription,”
Curtis Hawthorne, Erich Elsen, Jialin Song, Adam Roberts, Ian Simon, Colin Raffel, Jesse Engel, Sageev Oore, and Douglas Eck, · 2017
Earlier work this paper cites.
“Musicvae: Creating a palette for musical scores with machine learning, march 2018,” 2018
Adam Roberts, Jesse Engel, Colin Raffel, Ian Simon, and Curtis Hawthorne, · 2018
Earlier work this paper cites.
“Musegan: Multi-track sequential generative adversarial networks for symbolic music generation and accompaniment,”
Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang, · 2018
Earlier work this paper cites.
“GANSynth: Adversarial neural audio synthesis,”
Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, and Adam Roberts, · 2019
Earlier work this paper cites.
“Deep unsupervised drum transcription,”
Keunwoo Choi and Kyunghyun Cho, · 2019
Earlier work this paper cites.
“Enabling factorized piano music modeling and generation with the MAESTRO dataset,”
Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang, Sander Dieleman, Erich Elsen, Jesse Engel, and Douglas Eck, · 2019
Earlier work this paper cites.
Kin Wai Cheuk, Hans Anderson, Kat Agres, and Dorien Herremans, · 2019
Cited alongside, same era.
“Diffwave: A versatile diffusion model for audio synthesis,”
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro, · 2020
Cited alongside, same era.
“Wavegrad: Estimating gradients for waveform generation,”
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan, · 2020
Cited alongside, same era.
“Denoising diffusion probabilistic models,”
Jonathan Ho, Ajay Jain, and Pieter Abbeel, · 2020
Cited alongside, same era.
“The impact of audio input representations on neural network based music transcription,”
Kin Wai Cheuk, Kat Agres, and Dorien Herremans, · 2020
Cited alongside, same era.
“Classifier-free diffusion guidance,”
Jonathan Ho and Tim Salimans, · 2021
Later among the works it cites.
“Revisiting the onsets and frames model with additive attention,”
Kin Wai Cheuk, Yin-Jyun Luo, Emmanouil Benetos, and Dorien Herremans, · 2021
Later among the works it cites.
“The effect of spectrogram reconstruction on automatic music transcription: An alternative approach to improve transcription accuracy,”
Kin Wai Cheuk, Yin-Jvun Luo, Emmanouil Benetos, and Dorien Herremans, · 2021
Later among the works it cites.
“Jointist: Joint learning for multi-instrument transcription and its applications,”
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong, Bochen Li, Minz Won, Amy Hung, Ju-Chiang Wang, and Dorien Herremans, · 2022
Closest in time.
“Hppnet: Modeling the harmonic structure and pitch invariance in piano transcription,”
Weixing Wei, Peilin Li, Yi Yu, and Wei Li, · 2022
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Josh Gardner, Ian Simon, Ethan Manilow, Curtis Hawthorne, and Jesse Engel, · 2021
Cited alongside, same era.
“High-resolution piano transcription with pedals by regressing onset and offset times,”
Qiuqiang Kong, Bochen Li, Xuchen Song, Yuan Wan, and Yuxuan Wang, · 2021
Cited alongside, same era.
“Reconvat: A semi-supervised automatic music transcription framework for low-resource real-world data,”
Kin Wai Cheuk, Dorien Herremans, and Li Su, · 2021
Cited alongside, same era.
“Denoising diffusion implicit models,”
Jiaming Song, Chenlin Meng, and Stefano Ermon, · 2021
Cited alongside, same era.
“Zero-shot text-to-image generation,”
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever, · 2021
Cited alongside, same era.
“Symbolic music generation with diffusion models,”
Gautam Mittal, Jesse Engel, Curtis Hawthorne, and Ian Simon, · 2021
Cited alongside, same era.
“Skipping the frame-level: Event-based piano transcription with neural semi-CRFs,”
Yujia Yan, Frank Cwitkowitz, and Zhiyao Duan, · 2021
Cited alongside, same era.
“Unaligned supervision for automatic music transcription in the wild,”
Ben Maman and Amit H Bermano, · 2022
Closest in time.
“Semi-supervised convolutive nmf for automatic music transcription,”
Haoran Wu, Axel Marmoret, and Jérémy E Cohen, · 2022
Closest in time.
“Regularizing score-based models with score fokker-planck equations,”
Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, and Stefano Ermon, · 2022
Closest in time.
“Analog bits: Generating discrete data using diffusion models with self-conditioning,”
Ting Chen, Ruixiang Zhang, and Geoffrey Hinton, · 2022
Closest in time.
“Multi-instrument music synthesis with spectrogram diffusion,”
Curtis Hawthorne, Ian Simon, Adam Roberts, Neil Zeghidour, Josh Gardner, Ethan Manilow, and Jesse Engel, · 2022
Closest in time.
“Denoising diffusion restoration models,”
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song, · 2022
Closest in time.
“Progressive distillation for fast sampling of diffusion models,”
Tim Salimans and Jonathan Ho, · 2022
Closest in time.