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AI USE CASES

How to get a written description of any audio file with earshot

Turn a sound file into plain words, tags and measurements an agent can reason about.

Seen in the wild

Evidence: X, Oct 2026 · X, Oct 2026

Similar to what people reported. The steps and prompt below are AI written, not copied from those posts.

Who it is forBuilder with a folder of unlabeled sound files who needs to know what each one actually sounds like

The problemAn agent cannot open a .wav or .ogg and tell what it is, how long it rings or how bright it is.

The outcomeA short text reading with calibrated tags, closest alternative readings and numbers like peak level and brightness.

What you need first

  • Python
  • CPU only, no GPU needed
  • Local models load on first call (about 20 to 40 seconds per CLI call)
  • No account or paid key for core features
  • Optional Gemini key only for the `llm` command
  • Reference recordings for `forge --refset` are not in the repo; bring your own with `--refs DIR`

Steps

  1. Install earshot and run earshot doctor.
  2. Run earshot describe enter.ogg (swap in your file).
  3. Add --json if the agent needs the full structured result, or --out f.json to save it.
  4. Use the description to label or sort the file in your project.

Prompt for your agent

Use earshot to describe every audio file in <folder> and write a one-line label per file from the tags. Verify one label by listening or by running `earshot match` on it.

Caveat. Tags are model readings with a confidence score (z), so treat low-confidence results as hints, not facts.

About earshot

Gives coding agents ears: they can listen to audio, review it and generate sound. Runs on a plain CPU and is open source. View Leonxlnx/earshot on GitHub.

More with earshot

See all use cases for Leonxlnx/earshot

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