- Research Article
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A Discriminative Model for Polyphonic Piano Transcription
EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 048317 (2006)
We present a discriminative model for polyphonic piano transcription. Support vector machines trained on spectral features are used to classify frame-level note instances. The classifier outputs are temporally constrained via hidden Markov models, and the proposed system is used to transcribe both synthesized and real piano recordings. A frame-level transcription accuracy of 68% was achieved on a newly generated test set, and direct comparisons to previous approaches are provided.
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Poliner, G.E., Ellis, D.P.W. A Discriminative Model for Polyphonic Piano Transcription. EURASIP J. Adv. Signal Process. 2007, 048317 (2006) doi:10.1155/2007/48317
- Support Vector Machine
- Information Technology
- Support Vector
- Markov Model
- Spectral Feature