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• W2891901715 abstract "Fundamental frequency (f0) estimation from polyphonic music includes the tasks of multiple-f0, melody, vocal, and bass line estimation. Historically these problems have been approached separately, and only recently, using learning-based approaches. We present a multitask deep learning architecture that jointly estimates outputs for various tasks including multiple-f0, melody, vocal and bass line estimation, and is trained using a large, semi-automatically annotated dataset. We show that the multitask model outperforms its single-task counterparts, and explore the effect of various design decisions in our approach, and show that it performs better or at least competitively when compared against strong baseline methods." @default.
• W2891901715 created "2018-09-27" @default.
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• W2891901715 date "2018-09-02" @default.
• W2891901715 modified "2023-09-27" @default.
• W2891901715 title "Multitask Learning for Fundamental Frequency Estimation in Music" @default.
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• W2891901715 hasPublicationYear "2018" @default.
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