Enhancing chord classification through neighbourhood histograms | IEEE Conference Publication | IEEE Xplore

Enhancing chord classification through neighbourhood histograms


Abstract:

The chord progression of a song is an important high-level feature which enables indexing as well as deeper analysis of musical recordings. Different approaches to chord ...Show More

Abstract:

The chord progression of a song is an important high-level feature which enables indexing as well as deeper analysis of musical recordings. Different approaches to chord recognition have been suggested in the past. Though their performance increased, still significant error rates seem to be un-avoidable. One way to improve accuracy is to try to correct possible misclassifications. In this paper, we propose a post-processing method based on considerations of musical harmony, assuming that the pool of chords used in a song is limited and that strong oscillations of chords are uncommon. We show that exploiting (uncertain) knowledge about the chord-distribution in a chordpsilas neighbourhood can significantly improve chord detection accuracy by evaluating our proposed post-processing method for three baseline classifiers on two early Beatles albums.
Date of Conference: 18-20 June 2008
Date Added to IEEE Xplore: 15 July 2008
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Conference Location: London, UK

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