Audio Denoising
5 papers with code • 3 benchmarks • 0 datasets
Benchmarks
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Datasets
Greatest papers with code
Speech Denoising by Accumulating Per-Frequency Modeling Fluctuations
mosheman5/DNP
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The method is completely unsupervised and only trains on the specific audio clip that is being denoised.
Co-Separating Sounds of Visual Objects
rhgao/co-separation
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ICCV 2019
Learning how objects sound from video is challenging, since they often heavily overlap in a single audio channel.
Ranked #1 on
Audio Source Separation
on MUSIC (multi-source)
Learning to Separate Object Sounds by Watching Unlabeled Video
rhgao/Deep-MIML-Network
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ECCV 2018
Our work is the first to learn audio source separation from large-scale "in the wild" videos containing multiple audio sources per video.
Speech Denoising without Clean Training Data: a Noise2Noise Approach
madhavmk/Noise2Noise-audio_denoising_without_clean_training_data
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This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio-denoising methods by showing that it is possible to train deep speech denoising networks using only noisy speech samples.
On the Design of Deep Priors for Unsupervised Audio Restoration
vivsivaraman/designaudiopriors
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Unsupervised deep learning methods for solving audio restoration problems extensively rely on carefully tailored neural architectures that carry strong inductive biases for defining priors in the time or spectral domain.