Automatic transcription of piano music based on HMM tracking of jointly-estimated pitches
Abstract
This work deals with the automatic transcription of piano recordings into a MIDI symbolic file. The system consists of subsequent stages of onset detection and multipitch estimation and tracking. The latter is based on a Hidden Markov Model framework, embedding a spectral maximum likelihood method for joint pitch estimation. The complexity issue of joint estimation techniques is solved by selecting subsets of simultaneously played notes within a pre-estimated set of candidates. Tests on a large database and comparisons to state-of-the-art methods show promising results.
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