ReMi: A Random Recurrent Neural Network Approach to Music Production
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866909699575644160 |
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| author | Chateau-Laurent, Hugo Vanhatalo, Tara Pan, Wei-Tung Hinaut, Xavier |
| author_facet | Chateau-Laurent, Hugo Vanhatalo, Tara Pan, Wei-Tung Hinaut, Xavier |
| contents | Generative artificial intelligence raises concerns related to energy consumption, copyright infringement and creative atrophy. We show that randomly initialized recurrent neural networks can produce arpeggios and low-frequency oscillations that are rich and configurable. In contrast to end-to-end music generation that aims to replace musicians, our approach expands their creativity while requiring no data and much less computational power. More information can be found at: https://allendia.com/ |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_17023 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ReMi: A Random Recurrent Neural Network Approach to Music Production Chateau-Laurent, Hugo Vanhatalo, Tara Pan, Wei-Tung Hinaut, Xavier Sound Artificial Intelligence Audio and Speech Processing Generative artificial intelligence raises concerns related to energy consumption, copyright infringement and creative atrophy. We show that randomly initialized recurrent neural networks can produce arpeggios and low-frequency oscillations that are rich and configurable. In contrast to end-to-end music generation that aims to replace musicians, our approach expands their creativity while requiring no data and much less computational power. More information can be found at: https://allendia.com/ |
| title | ReMi: A Random Recurrent Neural Network Approach to Music Production |
| topic | Sound Artificial Intelligence Audio and Speech Processing |
| url | https://arxiv.org/abs/2505.17023 |