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Article Dans Une Revue IEEE Signal Processing Magazine Année : 2024

Model-Based Deep Learning for Music Information Research

Résumé

In this article, we investigate the notion of model-based deep learning in the realm of music information research (MIR). Loosely speaking, we refer to the term model-based deep learning for approaches that combine traditional knowledge-based methods with data-driven techniques, especially those based on deep learning, within a diff erentiable computing framework. In music, prior knowledge for instance related to sound production, music perception or music composition theory can be incorporated into the design of neural networks and associated loss functions. We outline three specifi c scenarios to illustrate the application of model-based deep learning in MIR, demonstrating the implementation of such concepts and their potential.
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Dates et versions

hal-04611461 , version 1 (13-06-2024)
hal-04611461 , version 2 (17-06-2024)

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  • HAL Id : hal-04611461 , version 2

Citer

Gael Richard, Vincent Lostanlen, Yi-Hsuan Yang, Meinard Müller. Model-Based Deep Learning for Music Information Research. IEEE Signal Processing Magazine, In press. ⟨hal-04611461v2⟩
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