arXiv Open Access 2025

ReMi: A Random Recurrent Neural Network Approach to Music Production

Hugo Chateau-Laurent Tara Vanhatalo Wei-Tung Pan Xavier Hinaut

Lihat Sumber

Abstrak

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/

Topik & Kata Kunci

cs.SD cs.AI eess.AS

Penulis (4)

Hugo Chateau-Laurent

Tara Vanhatalo

Wei-Tung Pan

Xavier Hinaut

Format Sitasi

APA MLA BibTeX

Chateau-Laurent, H., Vanhatalo, T., Pan, W., Hinaut, X. (2025). ReMi: A Random Recurrent Neural Network Approach to Music Production. https://arxiv.org/abs/2505.17023

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓