DEDUPEDWho it is forAudio-minded builder checking whether a sound in a project reads as a real recording or an obvious synthesis
The problemIt is hard to tell, without careful listening, whether a sound will pass as real or give itself away.
The outcomeA real versus synthesized verdict with evidence and per-window scores, plus a plain-words A/B of two sounds.
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
- Run
earshot realness FILE...on the files you want to check. - Run
earshot ab A Bto compare two sounds or two trims in words. - Run
earshot compare FILE --refs DIRto see the nearest reference recordings. - Use the findings to decide which sound to rework.
Prompt for your agent
Use earshot realness on <files> and earshot ab on the two closest candidates, then tell me which one reads as most real and why. Verify with a listening check, since the realness model can be fooled.
Caveat. The README warns the realness model is easy to fool (a modal resonator plus a room and noise floor reads as real), so do not treat the verdict as proof.
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
- Synthesize a new sound in code and refine it by ear Let the agent write a sound recipe, then have a critic score and improve it against real references.
- Pick the best sound from a pile of downloads Rank candidate files against a text description and trim the best moment from a long recording.
- Get a written description of any audio file Turn a sound file into plain words, tags and measurements an agent can reason about.
- Score a launch film's audio against pro launch films Run a scorecard that lists timestamped fixes for your film's soundtrack and mix.
- Turn a recording into code you can vary Fit a recording to a small synthesis model and get a Python recipe you can tweak or morph.
- Build a sound kit for a code-made film Pick one sound per role from a bank of 201 effects and render them with measured sync points.
- Give Claude Code ears with the MCP server Run earshot as an MCP server so your agent can listen without reloading models each call.
- Check that sound hits land on your video cuts Get a second-by-second listening transcript of a film and see if hits match the picture cuts.
Disclaimer
Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page