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earshot

Audio analysis and sound synthesis for coding agents, as CLI, Python API and MCP

Repository on GitHub ↗ (opens in a new tab)
Stars
1.6k
License
MIT
Last commit
Oct 2026
Last release
Oct 2026
Language
Python

Missed the latest GitHub check; these facts may be older.

Overview

earshot lets a coding agent hear audio: it describes files in words, matches them to text descriptions, finds moments in long recordings, and scores a film's sound against a profile of 7 launch films. It also synthesizes sounds from code recipes (`forge`), fits recordings to recipes (`fit`), and renders from a bank of 201 code-defined effects. It runs on CPU using CLAP and an AudioSet AST tagger.

Who it is for: Developers building code-made films or UI sound with coding agents

Strengths

  • Exposes the same tools as CLI, Python API and MCP server for Claude Code
  • Runs on CPU only; models are pinned revisions with safetensors weights, loaded offline after first fetch
  • sfx and kit commands render from the 201-sound bank with no models or network
  • README states its limits, including a coin-flip blind test and Goodhart risk in the critic

Weaknesses

  • Each CLI call reloads models, about 20-40 s; MCP or Python needed for many calls
  • First use downloads about 1.1 GB of models
  • Forge reference recordings are licensed and not in the repo; --refset needs a local registry
  • No published blind-test score for the v2 sounds; the v1 test used one listener

What it needs

  • no GPU
  • Needs Python 3.10+, ffmpeg, ffprobe, PyTorch (CPU), Hugging Face model download (first run)
  • Models: CLAP laion/larger_clap_general, MIT/ast-finetuned-audioset-10-10-0.4593, Gemini (optional audio critique)

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