audio-to-midi

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 …

First seen May 8, 2026

Installation

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

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 22

License LICENSE

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Package contents

Files included with this skill beyond the listing page.

skill md SKILL.md 4,500 B

docs SUMMARY.md 769 B

History

May 8, 2026 First seen on skills.sh

Sep 9, 2026 First recorded snapshot · 59 installs

SKILL.md

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