audio-11

Audio Denoising

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in audio-denoising-11

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AV-Bench - Wooden Horse

AV-Bench - Violin Yanni

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Most implemented papers

Co-Separating Sounds of Visual Objects

K. Grauman, Ruohan Gao•Mon Apr 15 2019

This work introduces a co-separation training paradigm that permits learning object-level sounds from unlabeled multi-source videos, and obtains state-of-the-art results on visually-guided audio source separation and audio denoising for the MUSIC, AudioSet, and AV-Bench datasets.

220

Content

AV-Bench - Guitar Solo

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Learning to Separate Object Sounds by Watching Unlabeled Video

K. Grauman, Ruohan Gao, R. Feris•Wed Apr 04 2018

This work is the first to learn audio source separation from large-scale "in the wild" videos containing multiple audio sources per video, and obtains state-of-the-art results on visually-aided audio sources separation and audio denoising.

296 0

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Speech Denoising without Clean Training Data: a Noise2Noise Approach

Anuj Tambwekar, M. M. Kashyap, Krishnamoorthy Manohara, S. Natarajan•Wed Apr 07 2021

This work shows that speech denoising deep neural networks can be successfully trained utilizing only noisy training audio, and it is revealed that such training regimes achieve superiorDenoising performance over conventional training regimes utilizing clean training audio targets, in cases involving complex noise distributions and low Signal-to-Noise ratios (high noise environments).

47 0

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On the Design of Deep Priors for Unsupervised Audio Restoration

Jayaraman J. Thiagarajan, V. Narayanaswamy, A. Spanias•Tue Apr 13 2021

This paper proposes a new U-Net based prior that does not impact either the network complexity or convergence behavior of existing convolutional architectures, yet leads to significantly improved restoration, and advocates the use of carefully designed dilation schedules and dense connections in the U- net architecture to obtain powerful audio priors.

6 0

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Self-supervised speech denoising using only noisy audio signals

Lei Li, Jiasong Wu, Qingchun Li, Guanyu Yang, L. Senhadji, H. Shu•Fri Oct 29 2021

Experimental results show that the proposed method not only eliminates the high dependence on clean targets of traditional audio denoising tasks, but also achieves on-par or better performance than other training strategies.

17 0

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BirdSoundsDenoising: Deep Visual Audio Denoising for Bird Sounds

Youshan Zhang, Jialu Li•Mon Oct 17 2022

The first to transfer the audio denoising problem into an image segmentation problem and propose a deep visual audio Denoising (DVAD) model, which achieves state-of-the-art performance and can be easily generalized to speech denoisation, audio separation, audio enhancement, and noise estimation.

21 0

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The Intel neuromorphic DNS challenge

G. Orchard, S. Shrestha, Jonathan Timcheck, D. B. Rubin, A. Kupryjanow, Lukasz Pindor, Timothy M. Shea, Mike Davies•Wed Mar 15 2023

The Intel Neuromorphic Deep Noise Suppression Challenge (Intel N-DNS Challenge), inspired by the Microsoft DNS Challenge, tackles a ubiquitous and commercially relevant task: real-time audio denoising.

37 0

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Complex Image Generation SwinTransformer Network for Audio Denoising

Youshan Zhang•Sat Aug 19 2023

A complex image generation SwinTransformer network is developed and structure similarity and detailed loss functions are imposed to generate high-quality images and an SDR loss is developed to minimize the difference between denoised and clean audios.

6 0

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