ASSDSPOct 30, 2020

Audio Dequantization Using (Co)Sparse (Non)Convex Methods

arXiv:2010.16386v25 citationsHas Code
Originality Synthesis-oriented
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This addresses audio dequantization, a previously neglected topic, but appears incremental as it builds on existing sparsity-based approaches.

The paper tackles the problem of audio dequantization by proposing new sparsity-based methods, including convex and non-convex approaches in synthesis and analysis variants, and evaluates them using SDR and PEMO-Q metrics.

The paper deals with the hitherto neglected topic of audio dequantization. It reviews the state-of-the-art sparsity-based approaches and proposes several new methods. Convex as well as non-convex approaches are included, and all the presented formulations come in both the synthesis and analysis variants. In the experiments the methods are evaluated using the signal-to-distortion ratio (SDR) and PEMO-Q, a perceptually motivated metric.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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