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On the evaluation of generative models in music

, и . Neural Computing and Applications, 32 (9): 4773--4784 (01.05.2020)
DOI: 10.1007/s00521-018-3849-7

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Chia-Chih Yang

Chia-Yuan Yang

Yang Li

Li Yang

Yang Li

 

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On the evaluation of generative models in music, и . Neural Computing and Applications, 32 (9): 4773--4784 (ноября 2018)MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks., , , и . CoRR, (2017)CCATMos: Convolutional Context-aware Transformer Network for Non-intrusive Speech Quality Assessment., , , и . INTERSPEECH, стр. 3318-3322. ISCA, (2022)MidiNet: A Convolutional Generative Adversarial Network for Symbolic-Domain Music Generation., , и . ISMIR, стр. 324-331. (2017)Revisiting the problem of audio-based hit song prediction using convolutional neural networks., , , , и . ICASSP, стр. 621-625. IEEE, (2017)Remixing Music with Visual Conditioning., и . ISM, стр. 181-188. IEEE, (2020)Self-Supervised Learning for Speech Enhancement Through Synthesis., , , и . ICASSP, стр. 1-5. IEEE, (2023)TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids., , , , , , , и . INTERSPEECH, стр. 4054-4058. ISCA, (2020)On the evaluation of generative models in music, и . Neural Computing and Applications, 32 (9): 4773--4784 (01.05.2020)A Fuzzy MOP Based Competence Set Expansion Method for Technology Roadmap Definitions., , , , , , , , , и . SoMeT, том 327 из Frontiers in Artificial Intelligence and Applications, стр. 173-182. IOS Press, (2020)