Listening To Music

Listening to music

Claude hears nothing, but it can render audio in the real engine and measure it. Set up the loop render → look → measure → change one thing → re-render, and keep a table of the numbers per version. A version is better when a number you chose beforehand moves by more than the take-to-take noise, and the spectrogram shows the same thing.

Requirements: Node with playwright and Chromium (preinstalled in Claude Code on the web), Python with librosa soundfile scipy matplotlib pillow, and for sheet music music21 verovio mir_eval cairosvg (pip install --break-system-packages librosa music21 verovio mir_eval cairosvg). The first render installs @strudel/web into ~/.cache/listening-to-music/. All scripts live in scripts/; run them with --help or read the docstring for options.

1. Render

S=/path/to/listening-to-music/scripts
node $S/render_strudel.mjs loop.js --out v1.wav --seconds 40 --warmup 4        # Strudel code
node $S/record_page.mjs page.html --click "#power" --out v1.wav --seconds 40 --warmup 8 \
     --query "station=house" --eval "window.__fm.setSeed(7)"                   # any Web Audio page

Both print peak level and flag clipping. A peak above 1.0 means the listener hears hard clipping; fix levels before judging anything else.

For a before/after comparison, fix the randomness (a seed hook via --eval) so both versions play the same material, and record each version twice.

2. Look

python3 $S/spectrogram.py v1.wav --out v1.png --from-onset --pyin-floor G3 --label v1

Then open v1.png with the image viewer. The top panel is a note-axis CQT spectrogram with the pYIN lead line, and the bottom panel is chroma. Compare it with the reference picture or the previous version side by side. The .npz next to it holds the numbers for step 3.

3. Measure

The clash scan is exact for the notes as written. rubs.py confirms them in the audio, where release tails and reverb add overlaps the note data does not show. Record harmony checks with percussion and noise textures muted in both versions: drum partials form their own peaks and hold a full mix at a rub share near 0.28 whatever the chords do. Use --warmup, 40 s or more, and two takes per version; --pair prints the take-to-take spread and says when a change is inside it.

Summed roughness (roughness.py) is a coarse overall measure. On Strudel FM (2026-09-24) it could not tell the harmony fix apart from take-to-take noise in sleep and house. On the same takes, the rub meter measured sleep −51%, ambient −33%, lofi −20% and house −13%, with spreads of 0.006–0.015. A loud bass drone dominates the roughness normalisation and hides a pad's rubs. Don't treat an unmoved roughness figure as proof that nothing changed.

Sheet music: notation out, notation in

Notation is the other way to hear. A score shows voicings, clusters (noteheads pushed sideways are seconds), register and rhythm at a glance, and Claude reads clean engraving accurately. All these scripts share one events JSON (layer, t0, t1, midi; times in bars).

node $S/render_strudel.mjs loop.js --events ev.json --cycles 8          # notes as written
python3 $S/score.py ev.json --out score.png --layers LEAD,KEYS,BASS --harmony   # engrave + analyse
python3 $S/transcribe.py take.wav --out mel.json --bpm 115              # notes as heard (melody)
python3 $S/compare_notes.py ev.json mel.json --ref-layer LEAD --cand-layer melody --align 1
python3 $S/read_score.py tune.musicxml --out ref.json                   # .mxl .mid .abc .krn, corpus:
python3 $S/to_strudel.py ref.json --out tune.js                         # score -> Strudel code

score.py --harmony prints each chord change with its pitches, music21's chord name, a Roman numeral in the detected key, and a rub flag. On Strudel FM the same four lofi bars went from 15 of 28 chord changes with a rub to 0 of 28 after the voicing fix, and the engraving showed why: the old Fmaj7 had its E and F side by side.

Measured on 2026-09-25 (compare_notes.py, onset within 0.05 bar and pitch within 50 cents):

So:

• Score images: read them yourself. Open the page and zoom into dense staves by cropping a 3× render or scan. Write ABC (K:, M:, L:, one V: per staff), convert it with read_score.py, re-engrave with score.py, and compare the two pictures bar by bar before using the notes. Use oemer only as a rough first pass, and never trust it unchecked.
• Transcription is monophonic. For chords and inner voices, read the generating code's events or the score. Splitting at re-attacks is on by default, because a re-struck piano note has no gap; switch it off with --no-split for leads with delay or echo.
• Unknown downbeat: a recording that starts mid-loop needs compare_notes.py --align N. It searches shifts up to N bars and prints the one used.