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Large Language ModelsAudio & SpeechQiita 機械学習Published: Oct 26, 2026, 10:01 JST

Claude Code hit 67.5% key match, missed the chorus

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Claude Code hit 67.5% key match, missed the chorus

3 Key Points

  1. What happened

    A hobbyist fed a 90-second J-POP mp3 to Claude Code and got tempo right first try, a key estimate of F major / D minor at 67.5%, and — after isolating vocals and bass with Meta's Demucs — a half-step modulation in the chorus lasting about 10 bars.

  2. Why it matters

    The tempo match and the 67.5% key estimate exceeded the 58.3% random baseline, but the chorus chord output collapsed to a single repeated chord, showing that an AI can return confident, verifiable numbers while a whole section is still wrong.

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Context & Analysis

The author's experiment grew out of three motivations: a song with no published chords that they wanted to arrange, curiosity about Claude's limits, and a desire to skip the tedious parts of transcription — writing out the main melody and chords — so they could get to the fun part, harmonizing. They fed an mp3 to Claude Code, which used librosa for tempo and chroma analysis, Demucs for source separation, basic-pitch for transcription, and MuseScore to produce a score. The key estimate of 67.5% was measured against a 58.3% random baseline, a technique the author found broadly useful for reading any metric. The first chord attempt produced a chorus stuck on a single chord, which the author recognized as implausible even without perfect pitch. Claude then measured whether pitch information survived in the mix and found it largely absent, prompting a switch from improving inference to improving input. After Demucs isolation, the song's half-step modulation appeared, matching what the author had felt but could not name. A separate workflow issue — telling Claude the goal was an a cappella arrangement — caused it to filter out notes below vocal range, leaving only 23 bass notes; moving that constraint from input to output raised the count to 190. The author concludes the real gain was not speed but a shift from copying to verifying, work that felt less like a grind.

FAQ
What tools did the author use to analyze the song?
The author used Claude Code for the analysis and scripting, Demucs (Meta's source-separation model) to split the track into drums, bass, other, and vocals, and MuseScore to generate sheet music. librosa and basic-pitch were also used for audio analysis and transcription.
Did the AI get the key right?
It estimated F major / D minor at 67.5%, which exceeded the 58.3% random baseline, so the author accepted it as the likely key. However, the second and third candidates were close at 65.9% and 65.3%, so the estimate was not definitive.
Why did the chord detection fail at first?
The author found that the original mix had little pitch information because distorted guitar, synths, and drums masked the harmonic content. After isolating vocals and bass with Demucs, the chord output improved from 4 chord types to 16 in the chorus and revealed a modulation.
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