Large-Scale Study of Chord Estimation Algorithms Based on Chroma Representation and HMM

This paper deals with the automatic estimation of chord progression over time of an audio file. From the audio signal, a set of chroma vectors representing the pitch content of the file over time is extracted. From these observations the chord progression is then estimated using hidden Markov models. Several methods are proposed that allow taking into account music theory, perception of key and presence of higher harmonics of pitch notes. The proposed methods are then compared to existing algorithms. A large-scale evaluation on 110 hand-labeled songs from the Beatles allows concluding on improvement over the state of the art.