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• W3191781868 abstract "This paper proposes a new benchmark task for generat-ing musical passages in the audio domain by using thedrum loops from the FreeSound Loop Dataset, which arepublicly re-distributable. Moreover, we use a larger col-lection of drum loops from Looperman to establish fourmodel-based objective metrics for evaluation, releasingthese metrics as a library for quantifying and facilitatingthe progress of musical audio generation. Under this eval-uation framework, we benchmark the performance of threerecent deep generative adversarial network (GAN) mod-els we customize to generate loops, including StyleGAN,StyleGAN2, and UNAGAN. We also report a subjectiveevaluation of these models. Our evaluation shows that theone based on StyleGAN2 performs the best in both objec-tive and subjective metrics." @default.
• W3191781868 created "2021-08-16" @default.
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• W3191781868 date "2021-08-03" @default.
• W3191781868 modified "2023-09-27" @default.
• W3191781868 title "A Benchmarking Initiative for Audio-Domain Music Generation Using the Freesound Loop Dataset" @default.
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• W3191781868 doi "https://doi.org/10.48550/arxiv.2108.01576" @default.
• W3191781868 hasPublicationYear "2021" @default.
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