# madhavmk/Noise2Noise-audio\_denoising\_without\_clean\_training\_data

<https://repo.masters-masters.com/en/repos/madhavmk/Noise2Noise-audio_denoising_without_clean_training_data>

[Home](https://repo.masters-masters.com/en) › [madhavmk](https://repo.masters-masters.com/en/owners/madhavmk) › [Noise2Noise-audio\_denoising\_without\_clean\_training\_data](https://repo.masters-masters.com/en/repos/madhavmk/Noise2Noise-audio_denoising_without_clean_training_data)

madhavmk/Noise2Noise-audio\_denoising\_without\_clean\_training\_data has 213 stars on GitHub. Its RepoMasters card: Prototype tier. Source code for the paper…

| Field | Value |
| --- | --- |
| Owner | [madhavmk](https://repo.masters-masters.com/en/owners/madhavmk) |
| Stars | 213 |
| Forks | 42 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2021 |
| Topics | speech-denoising, audio-denoising, speech-enhancement, audio-enhancement, noise-reduction, noise-removal, noise2noise, deep-learning, autoencoder, data-collection |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [madhavmk/Noise2Noise-audio\_denoising\_without\_clean\_training\_data](https://github.com/madhavmk/Noise2Noise-audio_denoising_without_clean_training_data) |

## Repository

Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing…

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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