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BCB15

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. In Yoshua Bengio and Yann LeCun, editors, 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings. 2015. URL: http://arxiv.org/abs/1409.0473.

BKK18

Shaojie Bai, J. Zico Kolter, and Vladlen Koltun. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. CoRR, 2018. URL: http://arxiv.org/abs/1803.01271, arXiv:1803.01271.

BED09

Mert Bay, Andreas F. Ehmann, and J. Stephen Downie. Evaluation of multiple-f0 estimation and tracking systems. In Keiji Hirata, George Tzanetakis, and Kazuyoshi Yoshii, editors, Proceedings of the 10th International Society for Music Information Retrieval Conference, ISMIR 2009, Kobe International Conference Center, Kobe, Japan, October 26-30, 2009, 315–320. International Society for Music Information Retrieval, 2009. URL: http://ismir2009.ismir.net/proceedings/PS2-21.pdf.

BMS+17

Rachel M. Bittner, Brian McFee, Justin Salamon, Peter Li, and Juan Pablo Bello. Deep salience representations for F0 estimation in polyphonic music. In Sally Jo Cunningham, Zhiyao Duan, Xiao Hu, and Douglas Turnbull, editors, Proceedings of the 18th International Society for Music Information Retrieval Conference, ISMIR 2017, Suzhou, China, October 23-27, 2017, 63–70. 2017. URL: https://brianmcfee.net/papers/ismir2017_salience.pdf.

Bro91

J. Brown. Calculation of a constant q spectral transform. JASA (Journal of the Acoustical Society of America), 89(1):425–434, 1991.

BP09

Juan-Jo Burred and Geoffroy Peeters. An adaptive system for music classification and tagging. In Proc. of LSAS (International Workshop on Learning the Semantics of Audio Signals). Graz, Austria, 2009.

CZ18

CJ Carr and Zack Zukowski. Generating albums with samplernn to imitate metal, rock, and punk bands. CoRR, 2018.

ChaconLG14

Carlos Eduardo Cancino Chacón, Stefan Lattner, and Maarten Grachten. Developing tonal perception through unsupervised learning. In ISMIR, 195–200. 2014.

CTP11

Christophe Charbuillet, Damien Tardieu, and Geoffroy Peeters. Gmm supervector for content based music similarity. In Proc. of DAFx (International Conference on Digital Audio Effects), 425–428. Paris, France, September 2011.

CFS16

Keunwoo Choi, György Fazekas, and Mark B. Sandler. Automatic tagging using deep convolutional neural networks. In Michael I. Mandel, Johanna Devaney, Douglas Turnbull, and George Tzanetakis, editors, Proceedings of the 17th International Society for Music Information Retrieval Conference, ISMIR 2016, New York City, United States, August 7-11, 2016, 805–811. 2016. URL: https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/07/009\_Paper.pdf.

Cho17

François Chollet. Xception: deep learning with depthwise separable convolutions. In 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017, 1800–1807. IEEE Computer Society, 2017. URL: https://doi.org/10.1109/CVPR.2017.195, doi:10.1109/CVPR.2017.195.

DK02

A. DeCheveigne and H. Kawahara. Yin, a fundamental frequency estimator for speech and music. JASA (Journal of the Acoustical Society of America), 111(4):1917–1930, 2002.

DCLT19

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. BERT: pre-training of deep bidirectional transformers for language understanding. In NAACL-HLT (1), 4171–4186. Association for Computational Linguistics, 2019.

Die14

Sander Dieleman. Recommending music on spotify with deep learning. Technical Report, Spotify, http://benanne.github.io/2014/08/05/spotify-cnns.html, 2014.

DS14

Sander Dieleman and Benjamin Schrauwen. End-to-end learning for music audio. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, 6964–6968. IEEE, 2014. URL: https://doi.org/10.1109/ICASSP.2014.6854950, doi:10.1109/ICASSP.2014.6854950.

DMP19

Chris Donahue, Julian J. McAuley, and Miller S. Puckette. Adversarial audio synthesis. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019. OpenReview.net, 2019. URL: https://openreview.net/forum?id=ByMVTsR5KQ.

DEP19

Guillaume Doras, Philippe Esling, and Geoffroy Peeters. On the use of u-net for dominant melody estimation in polyphonic music. In Proc. of First International Workshop on Multilayer Music Representation and Processing (MMRP19). Milan, Italy, January , 24-25 2019. URL: https://hal.science/hal-02457728/document.

DP19

Guillaume Doras and Geoffroy Peeters. Cover detection using dominant melody embeddings. In Arthur Flexer, Geoffroy Peeters, Julián Urbano, and Anja Volk, editors, Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR 2019, Delft, The Netherlands, November 4-8, 2019, 107–114. 2019. URL: http://archives.ismir.net/ismir2019/paper/000010.pdf.

DPZ10

Zhiyao Duan, Bryan Pardo, and Changshui Zhang. Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions. IEEE Trans. Speech Audio Process., 18(8):2121–2133, 2010. URL: https://doi.org/10.1109/TASL.2010.2042119, doi:10.1109/TASL.2010.2042119.

DefossezCSA23

Alexandre Défossez, Jade Copet, Gabriel Synnaeve, and Yossi Adi. High fidelity neural audio compression. Trans. Mach. Learn. Res., 2023.

DefossezUBB19

Alexandre Défossez, Nicolas Usunier, Léon Bottou, and Francis R. Bach. Demucs: deep extractor for music sources with extra unlabeled data remixed. CoRR, 2019. URL: http://arxiv.org/abs/1909.01174, arXiv:1909.01174.

EP07

Daniel P. W. Ellis and Graham E. Poliner. Identifying 'cover songs' with chroma features and dynamic programming beat tracking. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2007, Honolulu, Hawaii, USA, April 15-20, 2007, 1429–1432. IEEE, 2007. URL: https://doi.org/10.1109/ICASSP.2007.367348, doi:10.1109/ICASSP.2007.367348.

Elm90

Jeffrey L. Elman. Finding structure in time. Cogn. Sci., 14(2):179–211, 1990. URL: https://doi.org/10.1207/s15516709cog1402\_1, doi:10.1207/S15516709COG1402\_1.

EBD10

Valentin Emiya, Roland Badeau, and Bertrand David. Multipitch estimation of piano sounds using a new probabilistic spectral smoothness principle. IEEE Trans. Speech Audio Process., 18(6):1643–1654, 2010. URL: https://doi.org/10.1109/TASL.2009.2038819, doi:10.1109/TASL.2009.2038819.

EAC+19

Jesse H. Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, and Adam Roberts. Gansynth: adversarial neural audio synthesis. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019. OpenReview.net, 2019. URL: https://openreview.net/forum?id=H1xQVn09FX.

EHGR20

Jesse H. Engel, Lamtharn Hantrakul, Chenjie Gu, and Adam Roberts. DDSP: differentiable digital signal processing. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net, 2020. URL: https://openreview.net/forum?id=B1x1ma4tDr.

ECT+24

Zach Evans, CJ Carr, Josiah Taylor, Scott H. Hawley, and Jordi Pons. Fast timing-conditioned latent audio diffusion. In ICML. OpenReview.net, 2024.

FBR13

Benoit Fuentes, Roland Badeau, and Gaël Richard. Harmonic adaptive latent component analysis of audio and application to music transcription. IEEE Trans. Speech Audio Process., 21(9):1854–1866, 2013. URL: https://doi.org/10.1109/TASL.2013.2260741, doi:10.1109/TASL.2013.2260741.

Fuj99

Takuya Fujishima. Realtime chord recognition of musical sound: a system using common lisp music. In Proceedings of the 1999 International Computer Music Conference, ICMC 1999, Beijing, China, October 22-27, 1999. Michigan Publishing, 1999. URL: https://hdl.handle.net/2027/spo.bbp2372.1999.446.

GFR+20

Beat Gfeller, Christian Havnø Frank, Dominik Roblek, Matthew Sharifi, Marco Tagliasacchi, and Mihajlo Velimirovic. SPICE: self-supervised pitch estimation. IEEE ACM Trans. Audio Speech Lang. Process., 28:1118–1128, 2020. URL: https://doi.org/10.1109/TASLP.2020.2982285, doi:10.1109/TASLP.2020.2982285.

GPougetAbadieM+14

Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio. Generative adversarial networks. CoRR, 2014. URL: http://arxiv.org/abs/1406.2661, arXiv:1406.2661.

Got06

Masataka Goto. AIST annotation for the RWC music database. In ISMIR 2006, 7th International Conference on Music Information Retrieval, Victoria, Canada, 8-12 October 2006, Proceedings, 359–360. 2006.

GHNO02

Masataka Goto, Hiroki Hashiguchi, Takuichi Nishimura, and Ryuichi Oka. RWC music database: popular, classical and jazz music databases. In ISMIR 2002, 3rd International Conference on Music Information Retrieval, Paris, France, October 13-17, 2002, Proceedings. 2002. URL: http://ismir2002.ismir.net/proceedings/03-SP04-1.pdf.

GGBE24

Azalea Gui, Hannes Gamper, Sebastian Braun, and Dimitra Emmanouilidou. Adapting frechet audio distance for generative music evaluation. In ICASSP, 1331–1335. IEEE, 2024.

GSL19

Siddharth Gururani, Mohit Sharma, and Alexander Lerch. An attention mechanism for musical instrument recognition. In Arthur Flexer, Geoffroy Peeters, Julián Urbano, and Anja Volk, editors, Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR 2019, Delft, The Netherlands, November 4-8, 2019, 83–90. 2019. URL: http://archives.ismir.net/ismir2019/paper/000007.pdf.

HCL06

Raia Hadsell, Sumit Chopra, and Yann LeCun. Dimensionality reduction by learning an invariant mapping. In 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 17-22 June 2006, New York, NY, USA, 1735–1742. IEEE Computer Society, 2006. URL: https://doi.org/10.1109/CVPR.2006.100, doi:10.1109/CVPR.2006.100.

HZRS16

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, 770–778. IEEE Computer Society, 2016. URL: https://doi.org/10.1109/CVPR.2016.90, doi:10.1109/CVPR.2016.90.

HJA20

Jonathan Ho, Ajay Jain, and Pieter Abbeel. Denoising diffusion probabilistic models. In Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin, editors, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020. URL: https://proceedings.neurips.cc/paper/2020/hash/4c5bcfec8584af0d967f1ab10179ca4b-Abstract.html.

HA15

Elad Hoffer and Nir Ailon. Deep metric learning using triplet network. In Yoshua Bengio and Yann LeCun, editors, 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings. 2015. URL: http://arxiv.org/abs/1412.6622.

HZC+17

Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. Mobilenets: efficient convolutional neural networks for mobile vision applications. CoRR, 2017. URL: http://arxiv.org/abs/1704.04861, arXiv:1704.04861.

HNB13

Eric J. Humphrey, Oriol Nieto, and Juan Pablo Bello. Data driven and discriminative projections for large-scale cover song identification. In Alceu de Souza Britto Jr., Fabien Gouyon, and Simon Dixon, editors, Proceedings of the 14th International Society for Music Information Retrieval Conference, ISMIR 2013, Curitiba, Brazil, November 4-8, 2013, 149–154. 2013. URL: http://www.ppgia.pucpr.br/ismir2013/wp-content/uploads/2013/09/246\_Paper.pdf.

JHM+17

Andreas Jansson, Eric J. Humphrey, Nicola Montecchio, Rachel M. Bittner, Aparna Kumar, and Tillman Weyde. Singing voice separation with deep u-net convolutional networks. In Sally Jo Cunningham, Zhiyao Duan, Xiao Hu, and Douglas Turnbull, editors, Proceedings of the 18th International Society for Music Information Retrieval Conference, ISMIR 2017, Suzhou, China, October 23-27, 2017, 745–751. 2017. URL: https://ismir2017.smcnus.org/wp-content/uploads/2017/10/171\_Paper.pdf.

KZRS19

Kevin Kilgour, Mauricio Zuluaga, Dominik Roblek, and Matthew Sharifi. Fréchet audio distance: A reference-free metric for evaluating music enhancement algorithms. In INTERSPEECH, 2350–2354. ISCA, 2019.

KW14

Diederik P. Kingma and Max Welling. Auto-encoding variational bayes. In Yoshua Bengio and Yann LeCun, editors, 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings. 2014. URL: http://arxiv.org/abs/1312.6114.

Kla03

Anssi Klapuri. Multiple fundamental frequency estimation based on harmonicity and spectral smoothness. Speech and Audio Processing, IEEE Transactions on, 11(6):804–816, 2003.

KCI+20

Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, and Mark D. Plumbley. Panns: large-scale pretrained audio neural networks for audio pattern recognition. IEEE ACM Trans. Audio Speech Lang. Process., 28:2880–2894, 2020.

KW16

Filip Korzeniowski and Gerhard Widmer. Feature learning for chord recognition: the deep chroma extractor. In Michael I. Mandel, Johanna Devaney, Douglas Turnbull, and George Tzanetakis, editors, Proceedings of the 17th International Society for Music Information Retrieval Conference, ISMIR 2016, New York City, United States, August 7-11, 2016, 37–43. 2016. URL: https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/07/178\_Paper.pdf.

KMS+21

Khaled Koutini, Shahed Masoudian, Florian Schmid, Hamid Eghbal-zadeh, Jan Schlüter, and Gerhard Widmer. Learning general audio representations with large-scale training of patchout audio transformers. In Joseph Turian, Björn W. Schuller, Dorien Herremans, Katrin Kirchhoff, L. Paola Garc\'ıa-Perera, and Philippe Esling, editors, HEAR: Holistic Evaluation of Audio Representations, Virtual Event, December 13-14, 2021, volume 166 of Proceedings of Machine Learning Research, 65–89. PMLR, 2021. URL: https://proceedings.mlr.press/v166/koutini22a.html.

KSL+23

Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, and Kundan Kumar. High-fidelity audio compression with improved RVQGAN. In NeurIPS. 2023.

LPKN17

Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan Nam. Sample-level deep convolutional neural networks for music auto-tagging using raw waveforms. CoRR, 2017. URL: http://arxiv.org/abs/1703.01789, arXiv:1703.01789.

LYZ+24

Yizhi Li, Ruibin Yuan, Ge Zhang, Yinghao Ma, Xingran Chen, Hanzhi Yin, Chenghao Xiao, Chenghua Lin, Anton Ragni, Emmanouil Benetos, Norbert Gyenge, Roger B. Dannenberg, Ruibo Liu, Wenhu Chen, Gus Xia, Yemin Shi, Wenhao Huang, Zili Wang, Yike Guo, and Jie Fu. MERT: acoustic music understanding model with large-scale self-supervised training. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024. OpenReview.net, 2024. URL: https://openreview.net/forum?id=w3YZ9MSlBu.

LGL23

Xingchao Liu, Chengyue Gong, and Qiang Liu. Flow straight and fast: learning to generate and transfer data with rectified flow. In ICLR. OpenReview.net, 2023.

LMW+22

Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie. A convnet for the 2020s. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, 11966–11976. IEEE, 2022. URL: https://doi.org/10.1109/CVPR52688.2022.01167, doi:10.1109/CVPR52688.2022.01167.

LM19

Yi Luo and Nima Mesgarani. Conv-tasnet: surpassing ideal time-frequency magnitude masking for speech separation. IEEE ACM Trans. Audio Speech Lang. Process., 27(8):1256–1266, 2019. URL: https://doi.org/10.1109/TASLP.2019.2915167, doi:10.1109/TASLP.2019.2915167.

MKO+22

Matthew C. McCallum, Filip Korzeniowski, Sergio Oramas, Fabien Gouyon, and Andreas F. Ehmann. Supervised and unsupervised learning of audio representations for music understanding. In Preeti Rao, Hema A. Murthy, Ajay Srinivasamurthy, Rachel M. Bittner, Rafael Caro Repetto, Masataka Goto, Xavier Serra, and Marius Miron, editors, Proceedings of the 23rd International Society for Music Information Retrieval Conference, ISMIR 2022, Bengaluru, India, December 4-8, 2022, 256–263. 2022. URL: https://archives.ismir.net/ismir2022/paper/000030.pdf.

MB17

Brian McFee and Juan Pablo Bello. Structured training for large-vocabulary chord recognition. In Sally Jo Cunningham, Zhiyao Duan, Xiao Hu, and Douglas Turnbull, editors, Proceedings of the 18th International Society for Music Information Retrieval Conference, ISMIR 2017, Suzhou, China, October 23-27, 2017, 188–194. 2017. URL: https://ismir2017.smcnus.org/wp-content/uploads/2017/10/77\_Paper.pdf.

MSB18

Brian McFee, Justin Salamon, and Juan Pablo Bello. Adaptive pooling operators for weakly labeled sound event detection. IEEE ACM Trans. Audio Speech Lang. Process., 26(11):2180–2193, 2018. URL: https://doi.org/10.1109/TASLP.2018.2858559, doi:10.1109/TASLP.2018.2858559.

MKG+17

Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, and Yoshua Bengio. Samplernn: an unconditional end-to-end neural audio generation model. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings. OpenReview.net, 2017. URL: https://openreview.net/forum?id=SkxKPDv5xl.

MWPT19

Noam Mor, Lior Wolf, Adam Polyak, and Yaniv Taigman. A universal music translation network. In ICLR (Poster). OpenReview.net, 2019.

NALR21

Javier Nistal, Cyran Aouameur, Stefan Lattner, and Gaël Richard. VQCPC-GAN: variable-length adversarial audio synthesis using vector-quantized contrastive predictive coding. In WASPAA, 116–120. IEEE, 2021.

NAVL22

Javier Nistal, Cyran Aouameur, Ithan Velarde, and Stefan Lattner. Drumgan VST: A plugin for drum sound analysis/synthesis with autoencoding generative adversarial networks. Proc. of International Conference on Machine Learning ICML, Workshop on Machine Learning for Audio Synthesis, MLAS, 2022, 2022.

NLR20

Javier Nistal, Stefan Lattner, and Gaël Richard. DRUMGAN: synthesis of drum sounds with timbral feature conditioning using generative adversarial networks. In ISMIR, 590–597. 2020.

NLR21

Javier Nistal, Stefan Lattner, and Gaël Richard. Darkgan: exploiting knowledge distillation for comprehensible audio synthesis with gans. In ISMIR, 484–492. 2021.

NPA+24

Javier Nistal, Marco Pasini, Cyran Aouameur, Maarten Grachten, and Stefan Lattner. Diff-a-riff: musical accompaniment co-creation via latent diffusion models. CoRR, 2024.

NoePM20

Paul-Gauthier Noé, Titouan Parcollet, and Mohamed Morchid. CGCNN: complex gabor convolutional neural network on raw speech. In 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020, 7724–7728. IEEE, 2020. URL: https://doi.org/10.1109/ICASSP40776.2020.9054220, doi:10.1109/ICASSP40776.2020.9054220.

PP07

Hélène Papadopoulos and Geoffroy Peeters. Large-scale study of chord estimation algorithms based on chroma representation. In Proc. of IEEE CBMI (International Workshop on Content-Based Multimedia Indexing). Bordeaux, France, 2007.

PCDV20

Manuel Pariente, Samuele Cornell, Antoine Deleforge, and Emmanuel Vincent. Filterbank design for end-to-end speech separation. In 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020, 6364–6368. IEEE, 2020. URL: https://doi.org/10.1109/ICASSP40776.2020.9053038, doi:10.1109/ICASSP40776.2020.9053038.

PLF24

Marco Pasini, Stefan Lattner, and George Fazekas. Music2latent: consistency autoencoders for latent audio compression. CoRR, 2024. URL: https://doi.org/10.48550/arXiv.2408.06500, arXiv:2408.06500, doi:10.48550/ARXIV.2408.06500.

PSchluter22

Marco Pasini and Jan Schlüter. Musika! fast infinite waveform music generation. In ISMIR, 543–550. 2022.

PP13

Johan Pauwels and Geoffroy Peeters. Evaluating automatically estimated chord sequences. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, 749–753. IEEE, 2013. URL: https://doi.org/10.1109/ICASSP.2013.6637748, doi:10.1109/ICASSP.2013.6637748.

Pee04

Geoffroy Peeters. A large set of audio features for sound description (similarity and classification) in the cuidado project. Cuidado Project Report, Ircam, 2004.

Pee07

Geoffroy Peeters. A generic system for audio indexing: application to speech/ music segmentation and music genre. In In Proc. of DAFx (International Conference on Digital Audio Effects). Bordeaux, France, 2007.

PLS16

Jordi Pons, Thomas Lidy, and Xavier Serra. Experimenting with musically motivated convolutional neural networks. In 14th International Workshop on Content-Based Multimedia Indexing, CBMI 2016, Bucharest, Romania, June 15-17, 2016, 1–6. IEEE, 2016. URL: https://doi.org/10.1109/CBMI.2016.7500246, doi:10.1109/CBMI.2016.7500246.

RMH+14

Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, and Daniel P. W. Ellis. Mir_eval: A transparent implementation of common MIR metrics. In Hsin-Min Wang, Yi-Hsuan Yang, and Jin Ha Lee, editors, Proceedings of the 15th International Society for Music Information Retrieval Conference, ISMIR 2014, Taipei, Taiwan, October 27-31, 2014, 367–372. 2014. URL: http://www.terasoft.com.tw/conf/ismir2014/proceedings/T066\_320\_Paper.pdf.

RB18

Mirco Ravanelli and Yoshua Bengio. Speaker recognition from raw waveform with sincnet. In 2018 IEEE Spoken Language Technology Workshop, SLT 2018, Athens, Greece, December 18-21, 2018, 1021–1028. IEEE, 2018. URL: https://doi.org/10.1109/SLT.2018.8639585, doi:10.1109/SLT.2018.8639585.

RLHP23

Alain Riou, Stefan Lattner, Gaëtan Hadjeres, and Geoffroy Peeters. PESTO: pitch estimation with self-supervised transposition-equivariant objective. In Augusto Sarti, Fabio Antonacci, Mark Sandler, Paolo Bestagini, Simon Dixon, Beici Liang, Gaël Richard, and Johan Pauwels, editors, Proceedings of the 24th International Society for Music Information Retrieval Conference, ISMIR 2023, Milan, Italy, November 5-9, 2023, 535–544. 2023. URL: https://doi.org/10.5281/zenodo.10265343, doi:10.5281/ZENODO.10265343.

RFB15

Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: convolutional networks for biomedical image segmentation. In Nassir Navab, Joachim Hornegger, William M. Wells III, and Alejandro F. Frangi, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5 - 9, 2015, Proceedings, Part III, volume 9351 of Lecture Notes in Computer Science, 234–241. Springer, 2015. URL: https://doi.org/10.1007/978-3-319-24574-4\_28, doi:10.1007/978-3-319-24574-4\_28.

SKP15

Florian Schroff, Dmitry Kalenichenko, and James Philbin. Facenet: A unified embedding for face recognition and clustering. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7-12, 2015, 815–823. IEEE Computer Society, 2015. URL: https://doi.org/10.1109/CVPR.2015.7298682, doi:10.1109/CVPR.2015.7298682.

SerraGomez08

Joan Serrà and Emilia Gómez. Audio cover song identification based on tonal sequence alignment. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2008, March 30 - April 4, 2008, Caesars Palace, Las Vegas, Nevada, USA, 61–64. IEEE, 2008. URL: https://doi.org/10.1109/ICASSP.2008.4517546, doi:10.1109/ICASSP.2008.4517546.

Sey10

Klaus Seyerlehner. Content-Based Music Recommender Systems: Beyond simple Frame-Level Audio Similarity. PhD thesis, Johannes Kepler Universität, Linz, Austria, December 2010.

SUV18

Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani. Self-attention with relative position representations. In NAACL-HLT (2), 464–468. Association for Computational Linguistics, 2018.

SE03

A. Sheh and Daniel P. W. Ellis. Chord segmentation and recognition using em-trained hidden markov models. In Proc. of ISMIR (International Society for Music Information Retrieval), 183–189. Baltimore, Maryland, USA, 2003.

SED18

Daniel Stoller, Sebastian Ewert, and Simon Dixon. Wave-u-net: A multi-scale neural network for end-to-end audio source separation. In Emilia Gómez, Xiao Hu, Eric Humphrey, and Emmanouil Benetos, editors, Proceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018, Paris, France, September 23-27, 2018, 334–340. 2018. URL: http://ismir2018.ircam.fr/doc/pdfs/205\_Paper.pdf.

Stu13

Bob L. Sturm. The GTZAN dataset: its contents, its faults, their effects on evaluation, and its future use. CoRR, 2013. URL: http://arxiv.org/abs/1306.1461, arXiv:1306.1461.

SAL+24

Jianlin Su, Murtadha H. M. Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu. Roformer: enhanced transformer with rotary position embedding. Neurocomputing, 568:127063, 2024.

TLL+24

Modan Tailleur, Junwon Lee, Mathieu Lagrange, Keunwoo Choi, Laurie M. Heller, Keisuke Imoto, and Yuki Okamoto. Correlation of fréchet audio distance with human perception of environmental audio is embedding dependant. CoRR, 2024.

TC02

George Tzanetakis and Perry R. Cook. Musical genre classification of audio signals. IEEE Trans. Speech Audio Process., 10(5):293–302, 2002. URL: https://doi.org/10.1109/TSA.2002.800560, doi:10.1109/TSA.2002.800560.

vdODZ+16

Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew W. Senior, and Koray Kavukcuoglu. Wavenet: A generative model for raw audio. In Alan W. Black, editor, The 9th ISCA Speech Synthesis Workshop, SSW 2016, Sunnyvale, CA, USA, September 13-15, 2016, 125. ISCA, 2016. URL: https://www.isca-archive.org/ssw\_2016/vandenoord16\_ssw.html.

VSP+17

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett, editors, Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 5998–6008. 2017. URL: https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html.

VLBM08

Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol. Extracting and composing robust features with denoising autoencoders. In ICML, volume 307 of ACM International Conference Proceeding Series, 1096–1103. ACM, 2008.

Wak99

Gregory H. Wakefield. Mathematical representation of joint time-chroma distributions. In Proc. of SPIE conference on Advanced Signal Processing Algorithms, Architecture and Implementations, 637–645. Denver, Colorado, USA, 1999.

WP21

Christof Weiss and Geoffroy Peeters. Training deep pitch-class representations with a multi-label CTC loss. In Jin Ha Lee, Alexander Lerch, Zhiyao Duan, Juhan Nam, Preeti Rao, Peter van Kranenburg, and Ajay Srinivasamurthy, editors, Proceedings of the 22nd International Society for Music Information Retrieval Conference, ISMIR 2021, Online, November 7-12, 2021, 754–761. 2021. URL: https://archives.ismir.net/ismir2021/paper/000094.pdf.

WP22

Christof Weiss and Geoffroy Peeters. Comparing deep models and evaluation strategies for multi-pitch estimation in music recordings. Speech and Audio Processing, IEEE Transactions on, 2022. URL: https://arxiv.org/pdf/2202.09198.

WCZ+23

Yusong Wu, Ke Chen, Tianyu Zhang, Yuchen Hui, Taylor Berg-Kirkpatrick, and Shlomo Dubnov. Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation. In ICASSP, 1–5. IEEE, 2023.

YSerraGomez20

Furkan Yesiler, Joan Serrà, and Emilia Gómez. Accurate and scalable version identification using musically-motivated embeddings. In 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020, 21–25. IEEE, 2020. URL: https://doi.org/10.1109/ICASSP40776.2020.9053793, doi:10.1109/ICASSP40776.2020.9053793.

YK16

Fisher Yu and Vladlen Koltun. Multi-scale context aggregation by dilated convolutions. In Yoshua Bengio and Yann LeCun, editors, 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings. 2016. URL: http://arxiv.org/abs/1511.07122.

ZTdCQT21

Neil Zeghidour, Olivier Teboul, Félix de Chaumont Quitry, and Marco Tagliasacchi. LEAF: A learnable frontend for audio classification. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021. OpenReview.net, 2021. URL: https://openreview.net/forum?id=jM76BCb6F9m.