Does your AI-generated sound match the prompt? Local QA for generative audio — check, rank, QC, picture-fit and library search with EmbeddingGemma 2. CLI, web workbench, MCP server.
Install · Use · Workbench · AI agents · Reading a score · ⭐ Star
Does your AI-generated sound match what you asked for?
Sonicproof is a local QA tool for generative audio — sound effects, music and ambience from Stable Audio and friends. It listens with one multilingual model, Google's EmbeddingGemma 2, which puts text, sound, images and video in one shared space:
- check — does this clip sound like the prompt? Prompts can be in any language. - rank — you generated four seeds; which one should you keep? - qc — is it technically clean? Loudness, true peak, clipping, DC, silence, cut-off tails, clicks, phase, loop seams — with a one-line fix for every problem. - fit — does this sound suit the picture? A frame, a piece of concept art, a video clip, or a video's own soundtrack. - search — find sounds in your own library by words (any language), by example, or by picture. - dedupe — find the re-encoded, re-leveled and trimmed copies cluttering your library, and which one to keep.
Everything runs on your machine — no uploads, no API keys — and you can use it from a local workbench in your browser, from your AI agent (MCP server + agent skill), or from the command line and Python.
- Python 3.11 or newer (tested on 3.11–3.13). Apple Silicon (MPS), CUDA and CPU all work. sp is a short alias for sonicproof. - The model — EmbeddingGemma 2, about 1.5 GB — is downloaded from Hugging Face into its usual cache on first use. No Hugging Face account or token is needed. - ffmpeg is only needed for M4A / AAC / MP4 and other formats libsndfile can't read, and for video in fit / search. WA
From the project README.
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