AudioSnip
Cut Audio (all) in your browser — no upload, no server
What it does
AudioSnip is a free, web-based audio editor for trimming Audio files — entirely in your browser. No uploads, no accounts, no installs. - Visual waveform trimming - Smart Silence Remover — auto-detects and cuts silent gaps - Volume normalization - Export MP3 at 64–320 kbps - 100% client-side — your files never leave your device - Available in 10+ languages Perfect for podcasters, musicians & anyone needing quick audio edits without heavy software.
AudioSnip is a free web-based audio editor. Trim, normalize, and export MP3, WAV, OGG files entirely client-side without uploading to a server.
Securely trim, cut, and edit audio files directly in your browser. No uploads, no servers, maximum privacy. Drag and drop your file here or click the button below (Supports Audio &from audiosnip.dev
Does the same job
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- EVEdit videos faster by automatically removing silences2022 · kapwing.com · ▲171
Our team is filled with technologists and creators, and when we record and edit videos, 80% of the time is spent chopping up the video, removing silences, and picking the right takes. So we decided to build a tool that did that for you — or at least get you there most of the way! Our initial implementation is somewhat naïve and uses a user configurable silence threshold that just reads in volume levels. In the future, we’d like to use a frequency-based approach that focuses on the human voice. We’re also open to ideas, so let us know if you have any!



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Launched alongside, August 2026
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Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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