Publication | Closed Access
Evaluating automatically estimated chord sequences
26
Citations
13
References
2013
Year
Unknown Venue
MusicComputational MusicologyEngineeringMachine LearningEvaluation MetricsChord EstimationSpeech RecognitionInformation RetrievalData ScienceData MiningMirex CompetitionsOptical Music RecognitionChord SequencesHealth SciencesKnowledge DiscoveryAudio RetrievalComputer ScienceMusic ClassificationAlgorithmic CompositionSpeech Processing
In this paper, we perform an in-depth evaluation of a large number of algorithms for chord estimation that have been submitted to the MIREX competitions in 2010, 2011 and 2012. Therefore we first present a rigorous scheme to describe evaluation methods in a sound, unambiguous way that extends previous work specifically to take into account the large variance in chord estimation vocabularies and to perform evaluations on select sets of chords. Then we take a look at the evaluation metrics used so far and propose some alternative ones. Finally, we use these different methods to get a deeper insight into the strengths of each of the competing algorithms and show that the choice of evaluation measure greatly influences the ranking.
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