Chord Recognition using Instrument Voicing Constraints

This paper presents a technique of disambiguation for chord recognition based on a-priori knowledge of probabilities of chord voicings in the specific musical medium. The main motivating example is guitar chord recognition, where the physical layout and structure of the instrument, along with human physical and temporal constraints, make certain chord voicings and chord sequences more likely than others. Pitch classes are first extracted using the Pitch Class Profile (PCP) technique, and chords are then recognized using Artificial Neural Networks. The chord information is then analyzed using an array of voicing vectors (VV) indicating likelihood for chord voicings based on constraints of the instrument. Chord sequence analysis is used to reinforce accuracy of individual chord estimations. The specific notes of the chord are then inferred by combining the chord information and the best estimated voicing of the chord.