Chord Analyzer

Analyze music audio files to extract chord progressions, key signature, tempo, and song structure. Use when user wants to identify chords, analyze a song's harmony, or extract musical information from audio files (mp3, wav, m4a, etc.).

Chord Analyzer Skill

Analyze music audio files to extract chord progressions, key signature, tempo, and song structure.

When to Use

✅ USE this skill when:

• User wants to analyze a song's chords and harmony
• "What are the chords in this song?"
• "Analyze this audio file"
• "Extract the chord progression"
• "What key is this song in?"
• User provides an audio file path and asks for musical analysis

When NOT to Use

❌ DON'T use this skill when:

• Only wants general music info (lyrics, artist) → use web search
• Wants to generate music → use music generation skills
• Needs professional-grade transcription → recommend specialized software (Chordify, Hookpad)
• Requires detailed instrument separation → use dedicated source separation tools

Supported Formats

• Audio: mp3, wav, m4a, flac, ogg
• Duration: Works best for songs under 5 minutes

Installation

First time use requires installing dependencies:

bash

pip3 install librosa numpy scipy scikit-learn soundfile

Usage

Basic Analysis

bash

# Analyze an audio file
python3 chord_analyzer.py

# Edit the script to change the audio path
# Default: /Users/chentiewen/Music/网易云音乐/example.mp3

Script Integration

Copy the chord_analyzer.py script to your workspace and modify the audio_path variable:

python

audio_path = "/path/to/your/song.mp3"
result = analyze_audio(audio_path)

Output

The analyzer provides:

1. Key Signature: Detected musical key (e.g., C, F#m, G)
2. Tempo: Speed in BPM with rhythm classification
3. Chord Progression: Complete chord sequence with timestamps
4. Chord Statistics: Most frequently used chords
5. Song Structure: Intro/Verse/Outro segmentation (basic)

Sample Output

text

调性: F#m
速度: 123.0 BPM
节奏: 快板 (Allegro)

和弦走向:
F#mdim → A → D → Bm → E → A → D → Bm → E ...

主要和弦:
  A: 15次 (20.3%)
  E: 14次 (18.9%)
  D: 12次 (16.2%)

How It Works

1. Load Audio: Uses librosa.load() to read audio at 22.05kHz
2. Extract Chroma: Computes chroma features (pitch class profiles) using STFT
3. Detect Key: Analyzes chroma energy across all 12 keys (major + minor)
4. Track Tempo: Uses librosa.beat.beat_track() for tempo detection
5. Analyze Chords: Samples chroma at measure boundaries and matches against chord templates
6. Merge & Simplify: Combines consecutive identical chords

Limitations

• Accuracy: Chord detection is approximated; not professional-grade
• Complexity: Struggles with heavily layered or distorted music
• Structure: Simple segmentation (not verse/chorus detection)
• Melody: Does not extract melodic lines or instrument parts
• Chord Extensions: Detects basic triads (major, minor, diminished), not 7th/9th chords

For Complete Transcription

For professional music transcription, recommend:

• Chordify: https://chordify.net (online chord detection)
• Hookpad: https://www.hooktheory.com/hookpad (theory + chords)
• MuseScore: https://musescore.org (manual transcription)
• Capo: https://capoapp.com (slow down + chord detection)

Notes

• Analysis takes ~10-30 seconds depending on song length
• Best results with clear, non-distorted audio
• Works best for pop/rock/folk styles with clear harmony
• Not suitable for atonal, experimental, or heavily percussive music