DocumentCode :
1448449
Title :
Simultaneous Estimation of Chords and Musical Context From Audio
Author :
Mauch, Matthias ; Dixon, Simon
Author_Institution :
Centre for Digital Music, Queen Mary Univ. of London, London, UK
Volume :
18
Issue :
6
fYear :
2010
Firstpage :
1280
Lastpage :
1289
Abstract :
Chord labels provide a concise description of musical harmony. In pop and jazz music, a sequence of chord labels is often the only written record of a song, and forms the basis of so-called lead sheets. We devise a fully automatic method to simultaneously estimate from an audio waveform the chord sequence including bass notes, the metric positions of chords, and the key. The core of the method is a six-layered dynamic Bayesian network, in which the four hidden source layers jointly model metric position, key, chord, and bass pitch class, while the two observed layers model low-level audio features corresponding to bass and treble tonal content. Using 109 different chords our method provides substantially more harmonic detail than previous approaches while maintaining a high level of accuracy. We show that with 71% correctly classified chords our method significantly exceeds the state of the art when tested against manually annotated ground truth transcriptions on the 176 audio tracks from the MIREX 2008 Chord Detection Task. We introduce a measure of segmentation quality and show that bass and meter modeling are especially beneficial for obtaining the correct level of granularity.
Keywords :
Bayes methods; audio signal processing; MIREX 2008 chord detection task; audio waveform estimation; automatic method; chord-musical context; low-level audio features; model metric position; musical harmony; six-layered dynamic Bayesian network; Chord transcription; dynamic Bayesian networks (DBNs); music signal processing;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2009.2032947
Filename :
5256327
Link To Document :
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