Automatic Chord Detection Incorporating Beat and Key Detection

摘要

We introduce an algorithm that analyzes audio signals to extract chord-sequence information. The main goal of our approach lies in incorporating music theoretical knowlledge without restricting the input data to a narrow range of musical styles. At the basis of our approach lies pitch detection using enhanced autocorrelation, supported by key detection and beat tracking. The Chords themselves are identified by comparing generated and reference Pitch Class Profiles. A smoothing algorithm is applied to the chordsequence which optimizes the number of chord changes and thus takes into consideration the comparatively stable nature of chords. In this paper we present an evaluation performed on a large set of 35 pieces of diverse music showing an average performance of 65% accuracy.