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• W3117412552 abstract "Machine hearing is an emerging area. Motivated by the need of a principled framework across domain applications for machine listening, we propose a generic and data-driven representation learning approach. For this sake, a novel and efficient supervised dictionary learning method is presented. Experiments are performed on both computational auditory scene (East Anglia and Rouen) and synthetic music chord recognition datasets. Obtained results show that our method is capable to reach state-of-the-art hand-crafted features for both applications" @default.
• W3117412552 created "2021-01-05" @default.
• W3117412552 creator A5035273426 @default.
• W3117412552 date "2020-12-29" @default.
• W3117412552 modified "2023-09-27" @default.
• W3117412552 title "Data-driven audio recognition: a supervised dictionary approach." @default.
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