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Found 5 papers, 3 papers with code
Generating Sample-Based Musical Instruments Using Neural Audio Codec Language Models
In this paper, we propose and investigate the use of neural audio codec language models for the automatic generation of sample-based musical instruments based on text or reference audio prompts.
Continuous descriptor-based control for deep audio synthesis
Despite significant advances in deep models for music generation, the use of these techniques remains restricted to expert users.
Creativity in the era of artificial intelligence
As creativity is a highly context-prone concept, we underline the limits and deficiencies of current AI, requiring to move towards artificial creativity.
Ultra-light deep MIR by trimming lottery tickets
We show that our proposal can remove up to 90% of the model parameters without loss of accuracy, leading to ultra-light deep MIR models.
Diet deep generative audio models with structured lottery
This hypothesis states that extremely efficient small sub-networks exist in deep models and would provide higher accuracy than larger models if trained in isolation.
