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On the evaluation of generative models in music

, and . Neural Computing and Applications, 32 (9): 4773--4784 (May 1, 2020)
DOI: 10.1007/s00521-018-3849-7

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Revisiting the problem of audio-based hit song prediction using convolutional neural networks., , , , and . ICASSP, page 621-625. IEEE, (2017)Weight, Block or Unit? Exploring Sparsity Tradeoffs for Speech Enhancement on Tiny Neural Accelerators., , , , and . CoRR, (2021)Self-Supervised Learning for Speech Enhancement through Synthesis., , , and . CoRR, (2022)Remixing Music with Visual Conditioning., and . ISM, page 181-188. IEEE, (2020)TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids., , , , , , , and . INTERSPEECH, page 4054-4058. ISCA, (2020)Self-Supervised Learning for Speech Enhancement Through Synthesis., , , and . ICASSP, page 1-5. IEEE, (2023)MidiNet: A Convolutional Generative Adversarial Network for Symbolic-Domain Music Generation., , and . ISMIR, page 324-331. (2017)On the evaluation of generative models in music, and . Neural Computing and Applications, 32 (9): 4773--4784 (November 2018)MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions., , and . CoRR, (2017)Microarray meta-analysis database (M2DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database., , , , , , , , , and 1 other author(s). BMC Bioinform., (2010)