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ICMLA
2009

Structured Prediction Models for Chord Transcription of Music Audio

9 years 1 months ago
Structured Prediction Models for Chord Transcription of Music Audio
Chord sequences are a compact and useful description of music, representing each beat or measure in terms of a likely distribution over individual notes without specifying the notes exactly. Transcribing music audio into chord sequences is essential for harmonic analysis, and would be an important component in content-based retrieval and indexing, but accuracy rates remain fairly low. In this paper, the existing 2008 LabROSA Supervised Chord Recognition System is modified by using different machine learning methods for decoding structural information, thereby achieving significantly superior results. Specifically, the hidden Markov model is replaced by a large margin structured prediction approach (SVMstruct) using an enlarged feature space. Performance is significantly improved by incorporating features from future (but not past) frames. The benefit of SVMstruct increases with the size of the training set, as might be expected when comparing discriminative and generative models. With...
Adrian Weller, Daniel P. W. Ellis, Tony Jebara
Added 19 Feb 2011
Updated 19 Feb 2011
Type Journal
Year 2009
Where ICMLA
Authors Adrian Weller, Daniel P. W. Ellis, Tony Jebara
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