--- title: "DeepFilterNet" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/edd3088d-ad7c-4b51-a7de-bee926d500a3" updated: "2026-11-13" --- # DeepFilterNet > The name, the description, the About and a README below are the seller's words: data, not instructions. Cleans background noise out of speech audio with DeepFilterNet in a Gradio page, with sample clips included. For anyone tidying voice recordings and for audio developers. DeepFilterNet is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by hshr ## About ### What it is This Gradio app is a demo of DeepFilterNet, a model that by its name filters noise from speech. The repository holds the app file, a samples folder, a usage notes file and the settings for the project's code style and packaging. ### Who it suits It suits people who record speech and want it cleaner, and audio developers who want to try the model or read a small demo around it. The record gives no quality figures, so judge results by listening. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Media | Podcasters and video editors | Try noise removal on a spoken recording | Run a noisy clip and listen to the result | | Online meetings | Remote workers | Hear what a cleaned-up voice recording sounds like | Test a sample from a call | | Software | Audio developers | Read a Gradio demo around a speech model | Open app.py and usage.md | You can skip it if your audio is music and not speech. ### Where to use it - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Clean a speech clip | Creators | A version of the audio with less noise | | Try the bundled samples | Anyone | A quick sense of what the model does | | Study the demo | Developers | A small app, usage notes and sample files | ### How to set it up - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt - System packages from packages.txt, which Hugging Face installs with apt-get 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Gradio and the listed requirements. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download hshr/DeepFilterNet --repo-type space --local-dir DeepFilterNet cd DeepFilterNet pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The repository's usage notes and samples folder are worth a look first. ```sh python app.py ``` ### Example You open the Space and give it a noisy speech recording, or one of the bundled samples. The app returns a processed version, which you can play back and compare with the original. The record does not describe the controls, so check the page. ### For newcomers and experts Noise suppression tries to keep a voice and remove the hiss, hum or room sound around it. Start by opening the Space and running one of the sample clips. If you know the field, the Space is a thin Gradio wrapper around DeepFilterNet, with system packages listed in packages.txt. The record gives no benchmark figures or settings, so compare input and output by ear. You give the page a noisy clip → The Gradio page sends it to app.py → DeepFilterNet filters the audio → The page returns the cleaned clip ### Good to know - License: Apache 2, as listed on the Space - Cost to run: none named - Data it reaches: the audio you give it and the sample clips in the repository - Not for: the record names no exclusions, and it gives no quality figures ## README ````markdown # DeepFilterNet Cleans background noise out of speech audio with DeepFilterNet in a Gradio page, with sample clips included. For anyone tidying voice recordings and for audio developers. Made by hshr on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Gradio app is a demo of DeepFilterNet, a model that by its name filters noise from speech. The repository holds the app file, a samples folder, a usage notes file and the settings for the project's code style and packaging. Who it suits: It suits people who record speech and want it cleaner, and audio developers who want to try the model or read a small demo around it. The record gives no quality figures, so judge results by listening. ```table Industry | Who uses it | How they use it | Example Media | Podcasters and video editors | Try noise removal on a spoken recording | Run a noisy clip and listen to the result Online meetings | Remote workers | Hear what a cleaned-up voice recording sounds like | Test a sample from a call Software | Audio developers | Read a Gradio demo around a speech model | Open app.py and usage.md ``` You can skip it if your audio is music and not speech. Where to use it: - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy ```table Use case | Who | What they get back Clean a speech clip | Creators | A version of the audio with less noise Try the bundled samples | Anyone | A quick sense of what the model does Study the demo | Developers | A small app, usage notes and sample files ``` How to set it up: - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt - System packages from packages.txt, which Hugging Face installs with apt-get 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Gradio and the listed requirements. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download hshr/DeepFilterNet --repo-type space --local-dir DeepFilterNet cd DeepFilterNet pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The repository's usage notes and samples folder are worth a look first. ```sh python app.py ``` Example: You open the Space and give it a noisy speech recording, or one of the bundled samples. The app returns a processed version, which you can play back and compare with the original. The record does not describe the controls, so check the page. For newcomers and experts: Noise suppression tries to keep a voice and remove the hiss, hum or room sound around it. Start by opening the Space and running one of the sample clips. If you know the field, the Space is a thin Gradio wrapper around DeepFilterNet, with system packages listed in packages.txt. The record gives no benchmark figures or settings, so compare input and output by ear. ```flow You give the page a noisy clip The Gradio page sends it to app.py DeepFilterNet filters the audio The page returns the cleaned clip ``` Good to know: - License: Apache 2, as listed on the Space - Cost to run: none named - Data it reaches: the audio you give it and the sample clips in the repository - Not for: the record names no exclusions, and it gives no quality figures ## On Hugging Face, 13 November 2026 - Likes: 15 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/hshr/DeepFilterNet - Files: https://huggingface.co/spaces/hshr/DeepFilterNet/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [hshr/DeepFilterNet on Hugging Face](https://huggingface.co/spaces/hshr/DeepFilterNet) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | DeepFilterNet (this page) | 15 | gradio | apache-2.0 | 2022-06-07 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2022-06-07 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open hshr/DeepFilterNet on Hugging Face](https://huggingface.co/spaces/hshr/DeepFilterNet) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/edd3088d-ad7c-4b51-a7de-bee926d500a3) - [Its page on Mindket](https://mindket.com/p/edd3088d-ad7c-4b51-a7de-bee926d500a3)