arXiv:2403.04433
공식 코드 · Papers with Code
Tweaking autoregressive methods for inpainting of gaps in audio signals
원문 초록
A novel variant of the Janssen method for audio inpainting is presented and compared to other popular audio inpainting methods based on autoregressive (AR) modeling. Both conceptual differences and practical implications are discussed. The experiments demonstrate the importance of the choice of the AR model estimator, window/context length, and model order. The results show the superiority of the proposed gap-wise Janssen approach using objective metrics, which is confirmed by a listening test.
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Janssen 2.0: Audio Inpainting in the Time-frequency Domain
Diffusion-Based Audio Inpainting
Msanii: High Fidelity Music Synthesis on a Shoestring Budget
Solving Audio Inverse Problems with a Diffusion Model
Deep Audio Waveform Prior
Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization
토론
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