Presenter: Keunwoo Choi (https://keunwoochoi.github.io)
Slides: https://www.slideshare.net/KeunwooChoi/all-you-need-is-ai-and-music-by-keunwoo-choi

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0:06 👉 Introduction by Kyunghyun Cho

1:00 Keunwoo's starting / Abstract / Content

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3:31 👉 Starting the main content
3:40 What is Music AI?
* An On-line algorithm for real-time accompaniment, Roger Dannenberg, 1984, ICMC, https://www.cs.cmu.edu/~rbd/papers/icmc84accomp.pdf
7:14 2-by-2 Categorization of Music AI

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9:27 👉 Music AI - 1) Audio Synthesis
* Synthesizer / Three components of sound / Autoencoder
* DDSP: Differentiable Digital Signal Processing, Jesse Engel et al., 2019, ICLR, https://magenta.tensorflow.org/ddsp
* Tone Transfer https://sites.research.google/tonetransfer
* AI Sax Demo by Hanoi https://twitter.com/HanoiHantrakul/status/1258803013948342272
* Karasinger:Score-free singing voice synthesis with VQ-VAE using mel-spectrograms, 2021, Chien-Feng Liao, https://jerrygood0703.github.io/KaraSinger/
* RAVE: A variational autoencoder for fast and high-quality neural audio synthesis, Antoine Caillon and Philippe Esling, 2021, https://arxiv.org/abs/2111.05011

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31:08 👉 Music AI - 2) Creation
* Text-based LSTM networks for Automatic Music Composition, Keunwoo Choi et al., 2016, CSMC, https://arxiv.org/abs/1604.05358#
* Music Transformer: Generating Music with Long-Term Structure, Cheng-Zhi Anna Huang et al., 2019, ICLR, https://magenta.tensorflow.org/music-transformer
* MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer, Gino Brunner et al., 2018, ISMIR, https://arxiv.org/abs/1809.07600
* Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions, Yu-Siang Huang and Yi-Hsuan Yang, 2020, ACM MM, https://arxiv.org/abs/2002.00212

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48:27 👉 Music AI - 3) Audio Signal Processing
* Source Separation demo, Qiuqiang Kong, 2020, https://www.youtube.com/watch?v=WH4m5HYzHsg
* Steerable discovery of neural audio effects, Christian Steinmetz and Joshua Reiss, 2021, NeurIPS Creativity workshop, https://csteinmetz1.github.io/steerable-nafx/

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1:01:32 👉 Music AI - 4) Analysis
1:03:06 👉👉 Timbre Understanding
* MFCC, Convnets
* Automatic tagging using deep convolutional neural networks, Keunwoo Choi et al., 2016 ISMIR, https://arxiv.org/abs/1606.00298
* Music Classification Tutorial (https://music-classification.github.io/tutorial/)
1:17:47 👉👉 Note-level Understanding
* Onsets and Frames: Dual-Objective Piano Transcription, Curtis Hawthorne et al., 2018 ISMIR, https://arxiv.org/abs/1710.11153
* Polyphonic Piano Transcription Using Autoregressive Multi-State Note Model, Taegyun Kwon et al., 2020 ISMIR, https://arxiv.org/abs/2010.01104
* High-resolution Piano Transcription with Pedals by Regressing Onset and Offset Times, Qiuqiang Kong et al., 2020, https://arxiv.org/abs/2010.01815
* The MAESTRO Dataset and Wave2Midi2Wave, Curtis Hawthorne et al., ICLR 2019, https://magenta.tensorflow.org/maestro-wave2midi2wave
* Deep Unsupervised Drum Transcription, Keunwoo Choi and Kyunghyun Cho, ISMIR 2019, https://arxiv.org/abs/1906.03697
1:33:44 👉👉 Lyric Understanding

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1:35:08 👉 Conclusion
* ISMIR2021 Lab Showcase https://ismir2021.ismir.net/labshowcase/