/music-emotion — Emotion & Style Analysis

Classify the emotional content of an audio file: primary mood, energy level, emotional valence, arousal, genre, and mood tags.

Usage

/music-emotion <audio_file_path>

Steps

1. Validate the audio file path
2. Run emotion analysis:

python3 -m music_analyzer emotion "<audio_file_path>"

3. Present results:
   • Primary Emotion: Dominant mood (happy, sad, calm, energetic, etc.)
   • Energy Level: 0-1 scale with curve across song segments
   • Valence: -1 (negative) to 1 (positive)
   • Genre: Detected genre
   • Mood Tags: Descriptive mood keywords

Detection Methods

• CLAP (full tier): AI-based emotion/genre classification using CLAP model
• Heuristic (lite tier): Spectral features + rhythm + tonality-based rules

The method used is noted in the method field of the output.

Output Fields