HPCP-based music classification

Chord chroma representations have proven quite successful for chords detection from audio as they allow to infer chord labels1. These chroma representations, and more specifically Harmonic Pitch Class Profiles (HPCPs), can also be derived from chords in symbolic notation (eg [E2 G# 3 B3 E4]). Paiement et al. 2 have shown how the Euclidian distance between HPCPs matches perceptual closeness of chords. We are therefore interested in using HPCPs as a lowdimensional representation of chords in a “psycho-acoustic space”, for the purpose of classifying music based on harmonic information owing to Machine Learning techniques.