Optimized intellectual natural language processing using automated chord tag construction for auto accompaniment in music
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16101-6.pdf
Reference34 articles.
1. Aljanaki A, Soleymani M (2018) A data-driven approach to mid-level perceptual musical feature modeling. arXiv preprint arXiv:1806.04903. https://doi.org/10.48550/arXiv.1806.04903
2. Aljunid MF, Doddaghatta HM (2020) Multi-model deep learning approach for collaborative filtering recommendation system. CAAI Trans Intell Technol 5(4):268–275. https://doi.org/10.1049/trit.2020.0031
3. Bayle Y, Robine M, Hanna P (2019) SATIN: a persistent musical database for music information retrieval and a supporting deep learning experiment on song instrumental classification. Multimed Tools Appl 78(3):2703–2718. https://doi.org/10.1007/s11042-018-5797-8
4. Bisharad D, Laskar RH (2019) Music genre recognition using convolutional recurrent neural network architecture. Expert Syst 36(4):e12429. https://doi.org/10.1111/exsy.12429
5. Briot JP, Pachet F (2020) Deep learning for music generation: challenges and directions. Neural Comput Appl 32(4):981–993. https://doi.org/10.1007/s00521-018-3813-6
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Grey Wolf Optimizer Based Deep Learning Mechanism for Music Composition with Data Analysis;Applied Soft Computing;2024-01
2. Chord-based music generation using long short-term memory neural networks in the context of artificial intelligence;The Journal of Supercomputing;2023-10-16
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