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LVNS-RAVE: Diversified audio generation with RAVE and Latent Vector Novelty Search
April 23, 2024, 4:43 a.m. | Jinyue Guo, Anna-Maria Christodoulou, Balint Laczko, Kyrre Glette
cs.LG updates on arXiv.org arxiv.org
Abstract: Evolutionary Algorithms and Generative Deep Learning have been two of the most powerful tools for sound generation tasks. However, they have limitations: Evolutionary Algorithms require complicated designs, posing challenges in control and achieving realistic sound generation. Generative Deep Learning models often copy from the dataset and lack creativity. In this paper, we propose LVNS-RAVE, a method to combine Evolutionary Algorithms and Generative Deep Learning to produce realistic and novel sounds. We use the RAVE model …
abstract algorithms arxiv audio audio generation challenges control copy cs.lg cs.ne cs.sd deep learning designs eess.as evolutionary algorithms generative however limitations search sound tasks tools type vector
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