Claude Sound Ear — AI skill for Claude Code
Give your Claude eyes and ears on audio.
How to install Claude Sound Ear
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open thetoyosibello/claude-sound-ear and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Claude Sound Ear does
Give your Claude eyes and ears on audio. An installable Claude skill that turns any audio or video soundtrack into things an AI can actually reason over — a readable spectrogram, objective loudness/timing facts, a semantic map of every sound effect, offline speech transcription, and sound-driven cymatic visuals.
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README
sound-ear
**Give Claude eyes and ears on audio.** An installable [Claude](https://claude.com/product/claude-code) skill that turns any audio or video soundtrack into things an AI can actually reason over — a readable spectrogram, objective loudness/timing facts, a semantic map of every sound effect, offline speech transcription, and sound-driven cymatic visuals (including seamless long-form loops for sleep/ambient channels).
Claude can't natively *hear* a `.wav`, but it can read images and structured text. sound-ear converts sound into exactly those, then Claude reasons over the result.
What it does
| Command | Purpose | Needs |
|---|---|---|
hear.sh see |
Spectrogram + waveform + loudness/silence/scene-cut report | ffmpeg |
hear.sh map |
Semantic sound map: every SFX with timestamp, label, description, mix flags | Vertex or CLAP |
hear.sh transcribe |
Offline speech-to-text | faster-whisper |
hear.sh cymatics |
Sound-driven visuals (any aspect ratio) | numpy + PIL + ffmpeg |
hear.sh loop --minutes N |
Seamless long-form loop (sleep/ambient) rendered from a short seed | numpy + PIL + ffmpeg |
hear.sh doctor |
Device-compatibility report + engine routing | — |
Timing always comes from ffmpeg / spectral-flux onset detection, never from the language model (audio LLMs describe sound well but localize it poorly), so timestamps stay accurate.
Device-aware by design
Run `hear.sh doctor` and the skill reports what your machine supports and picks the best available engine for `map`:
- vertex — Gemini on your own Google Cloud (best quality). Needs
google-genai+ ADC. - clap — offline zero-shot labeling. Needs PyTorch + transformers.
If neither is present it falls back to `see` (visual) and `transcribe` (speech), which run anywhere with ffmpeg.
Install
git clone https://github.com/tysitv/claude-sound-ear.git ~/.claude/skills/sound-ear
cd ~/.claude/skills/sound-ear
./se
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