Browse State-of-the-Art › Audio Signal Processing
Audio Signal Processing
26 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
This is a general task that covers transforming audio inputs into audio outputs, not limited to existing PaperWithCode categories of Source Separation, Denoising, Classification, Recognition, etc.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
3 subtasks in the archive's task tree.
Most implemented papers archive 2025-07-28
26 shown of 26 papers with code (70 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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24 Oct 2022 6 repositories listedWe introduce a state-of-the-art real-time, high-fidelity, audio codec leveraging neural networks.
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11 May 2021 2 repositories listedWe present a data-driven approach to automate audio signal processing by incorporating stateful third-party, audio effects as layers within a deep neural network.
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11 Apr 2025 1 repository listedIn response, we introduce TorchFX: a GPU-accelerated Python library for DSP, specifically engineered to facilitate sophisticated audio signal processing.
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4 Oct 2024 1 repository listedIn this dataset, we used a digital stethoscope to capture both heart and lung sounds, including individual and mixed recordings.
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16 Sep 2024 1 repository listedAlthough deep reinforcement learning (DRL) approaches in audio signal processing have seen substantial progress in recent years, audio-driven DRL for tasks such as navigation, gaze control and head-orientation control…
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30 May 2024 1 repository listedThe combination of frequency-axis normalization with Min/Max scaling and the Mean Absolute Error (MAE) loss function achieved the highest Source-to-Distortion Ratio (SDR) of 7.
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27 Jan 2024 1 repository listedLeveraging large models, these data augmentation techniques have outperformed traditional approaches.
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2 Jan 2024 1 repository listedExperimental results demonstrate HAAQI-Net's effectiveness, achieving a Linear Correlation Coefficient (LCC) of 0.
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22 Dec 2023 1 repository listed Syntology ran 6 of 6 samples · 0 unverifiedIn neural audio signal processing, pitch conditioning has been used to enhance the performance of synthesizers.
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19 Sep 2023 1 repository listedAndroid device users can use this application without any cost, which will pave the way to ensure the safety of women and children.
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11 Sep 2023 1 repository listedNumerical simulations align with our theory and suggest that the condition number of a convolutional layer follows a logarithmic scaling law between the number and length of the filters, which is reminiscent of discrete…
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16 Jun 2023 1 repository listedWe introduce Multi-level feature Fusion-based Periodicity Analysis Model (MF-PAM), a novel deep learning-based pitch estimation model that accurately estimates pitch trajectory in noisy and reverberant acoustic…
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22 May 2023 1 repository listedThe obtained subspace is low-dimensional and has a surprisingly simple structure even for complex, non-invertible transformations of the input, leading to an exceptionally high efficiency of subspace-configurable…
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30 Jan 2023 1 repository listedIn the development of acoustic signal processing algorithms, their evaluation in various acoustic environments is of utmost importance.
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6 May 2022 1 repository listedSynthesizer is a type of electronic musical instrument that is now widely used in modern music production and sound design.
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27 Apr 2021 1 repository listedLinear operations on coefficients in the spherical harmonics (SH) transform domain that again yield SH-domain coefficients are an important toolset in many disciplines of research and engineering.
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23 Apr 2021 1 repository listedBy obtaining state-of-the-art results on a set of paralinguistics tasks, we demonstrate the suitability of the proposed transfer learning approach for embedded audio signal processing, even when data is scarce.
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12 Apr 2021 1 repository listedThe L3DAS21 Challenge is aimed at encouraging and fostering collaborative research on machine learning for 3D audio signal processing, with particular focus on 3D speech enhancement (SE) and 3D sound localization and…
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30 Jan 2021 1 repository listedWe present Melon Playlist Dataset, a public dataset of mel-spectrograms for 649, 091tracks and 148, 826 associated playlists annotated by 30, 652 different tags.
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27 Oct 2020 1 repository listedWe then compare different upsampling layers, showing that nearest neighbor upsamplers can be an alternative to the problematic (but state-of-the-art) transposed and subpixel convolutions which are prone to introduce…
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20 Jul 2020 1 repository listedDisentangling and recovering physical attributes, such as shape and material, from a few waveform examples is a challenging inverse problem in audio signal processing, with numerous applications in musical acoustics as…
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10 Jun 2020 1 repository listedDeep neural networks have shown promise for music audio signal processing applications, often surpassing prior approaches, particularly as end-to-end models in the waveform domain.
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28 May 2019 1 repository listedIn this work we present a data-driven approach for predicting the behavior of (i.
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30 Apr 2019 1 repository listedGiven the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing.
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31 Jan 2019 1 repository listedA typical audio signal processing pipeline includes multiple disjoint analysis stages, including calculation of a time-frequency representation followed by spectrogram-based feature analysis.
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6 Nov 2018 1 repository listedIn audio signal processing, probabilistic time-frequency models have many benefits over their non-probabilistic counterparts.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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