Harmonic pitch class profiles (HPCP) is a group of features that a computer program extracts from an audio signal, based on a pitch class profile—a descriptor proposed in the context of a chord recognition system.
[1] HPCP are an enhanced pitch distribution feature that are sequences of feature vectors that, to a certain extent, describe tonality, measuring the relative intensity of each of the 12 pitch classes of the equal-tempered scale within an analysis frame.
By processing musical signals, software can identify HPCP features and use them to estimate the key of a piece,[2] to measure similarity between two musical pieces (cover version identification),[3] to perform content-based audio retrieval (audio matching),[4] to extract the musical structure (audio structure analysis),[5] and to classify music in terms of composer, genre or mood.
The result of HPCP computation is a 12, 24, or 36-bin octave-independent histogram depending on the desired resolution, representing the relative intensity of each 1, 1/2, or 1/3 of the 12 semitones of the equal tempered scale.
The HPCP feature has been used to compute similarity between two songs in many research papers.