Artificial intelligence music generation model and method for configuring the same
US12354576B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 6, 2024 |
| Grant date | Jul 8, 2025 |
| Priority date | — |
| Expiry date | Aug 6, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10H2250/311
- WIPO fieldOther consumer goods
- WIPO sectorOther fields
Abstract
The present disclosure provides a method for configuring a learning model for music generation and the corresponding learning model. The method includes training a masked autoencoder with training data comprising a combination of a reconstruction loss over time and frequency domains and a patch-based adversarial objective operating at different resolutions. An omnidirectional latent diffusion model is trained based on music data represented in a latent space to obtain a pretrained diffusion model. The pretrained diffusion model is fine-tuned based on text-guided music generation, bidirectional music in-painting, and unidirectional music continuation. The method enables high-fidelity music generation conditioned on text or music representations while maintaining computational efficiency.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.