Audio to midi

Skill maystudios/claude-skills/audio-to-midi

Production-ready Claude Code skills for Unreal Engine 5, llama.cpp, and OpenCode CLI integration. Built by maystudios.

Install

npx -y skills add maystudios/claude-skills --skill audio-to-midi

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Convert MP3/WAV/FLAC audio files to MIDI (.mid) and MusicXML (.musicxml) with full music analysis. Two engines: Basic Pitch (general-purpose polyphonic) and Piano Model (high-accuracy piano, 96.7% F1). Optional Demucs stem separation. Use --engine piano for piano/keyboard music for best results. Trigger when the user wants to: transcribe audio to MIDI, convert music to sheet music/notes, extract notes from audio, get MusicXML from a recording, analyze tempo/key/chords of a song, separate stems (vocals/drums/bass) and transcribe each, or any audio-to-notation task. Also triggers for requests like "convert this MP3 to MIDI", "get the notes from this song", "what key is this song in", "transcribe this audio", "separate and transcribe stems".

SKILL.md

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Audio-to-MIDI Transcription

Convert audio files to MIDI and MusicXML with full music analysis (tempo, key, chords, dynamics, instruments).

Tool

Script: scripts/transcribe.py -- wraps Basic Pitch, Demucs, librosa, and music21. Auto-installs dependencies.

Workflow

Identify the input audio file (MP3, WAV, FLAC, OGG, M4A)
Determine options:
- Stems? Add --stems to separate vocals/drums/bass/other with Demucs first
- Output dir? Use -o path or default to input file's directory
- Skip analysis? Add --no-analysis if only MIDI/MusicXML needed
- Skip MusicXML? Add --no-musicxml if only MIDI needed
Run the transcription script
Report output files and analysis summary to user

Engines

Engine	Flag	Best for	Accuracy
Basic Pitch	`--engine basic-pitch` (default)	Mixed/polyphonic music	Good
Piano Model	`--engine piano`	Piano/keyboard music	96.7% F1

For piano or keyboard music, always use --engine piano — it captures sustain/pedal, has far fewer ghost notes, and produces much more accurate MIDI.

Usage

# Piano music (recommended for piano/keyboard)
py -3.12 scripts/transcribe.py "piano.mp3" --engine piano

# General music (default engine: Basic Pitch)
py -3.12 scripts/transcribe.py "song.mp3"

# With stem separation (Demucs): each stem gets its own MIDI + MusicXML
py -3.12 scripts/transcribe.py "song.wav" --stems

# Custom output directory
py -3.12 scripts/transcribe.py "song.mp3" -o ./output --engine piano

# Tuning Basic Pitch sensitivity
py -3.12 scripts/transcribe.py "song.mp3" --onset-threshold 0.6 --frame-threshold 0.4

# MIDI only (skip MusicXML)
py -3.12 scripts/transcribe.py "song.mp3" --no-musicxml

# MIDI + MusicXML without analysis
py -3.12 scripts/transcribe.py "song.mp3" --no-analysis

Output Files

For input song.mp3:

song.mid -- MIDI file (for DAWs, notation software)
song.musicxml -- MusicXML (for MuseScore, Finale, Sibelius, Dorico)
song_analysis.json -- Full analysis (tempo, key, chords, dynamics, spectral)

With --stems, each stem produces its own MIDI + MusicXML:

vocals.mid, vocals.musicxml
drums.mid, drums.musicxml
bass.mid, bass.musicxml
other.mid, other.musicxml

Analysis Output

The _analysis.json contains:

tempo_bpm: Detected BPM
key: Detected key and mode (e.g. "A minor")
key_confidence: 0-1 confidence score
chords: Time-stamped chord progression
unique_chords: Deduplicated chord list
dynamics: Mean/max/min dB, dynamic range
spectral: Centroid, bandwidth, rolloff, ZCR
instrument_hints: Detected instrument categories

Tuning Parameters

Flag	Default	Effect
`--onset-threshold`	0.5	Higher = fewer ghost notes, may miss quiet notes
`--frame-threshold`	0.3	Higher = stricter note detection
`--min-note-length`	58	Minimum note duration in ms

For clean recordings (piano, guitar): defaults work well. For complex mixes: use --stems for best results. For percussive music: lower onset threshold to 0.3-0.4.

Dependencies

Auto-installed on first run: basic-pitch, librosa, music21, pretty_midi, numpy, onnxruntime. With --stems: also installs demucs (includes PyTorch). Requires: Python 3.12 (py -3.12), ffmpeg (for MP3 decoding).

Important: Use py -3.12 (not python) to run the script. Python 3.14 has compatibility issues with ML packages. The script auto-selects the ONNX backend for Basic Pitch (most compatible).

Supported Input Formats

MP3, WAV, FLAC, OGG, M4A, AAC, WMA