Note separation of polyphonic music by energy split
ISPRA'08 Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation
Polyphonic music separation based on the simplified energy splitter
WSEAS Transactions on Signal Processing
Music scene-adaptive harmonic dictionary for unsupervised note-event detection
IEEE Transactions on Audio, Speech, and Language Processing
Adaptive harmonic spectral decomposition for multiple pitch estimation
IEEE Transactions on Audio, Speech, and Language Processing
Multipitch estimation of piano sounds using a new probabilistic spectral smoothness principle
IEEE Transactions on Audio, Speech, and Language Processing
What signal processing can do for the music
CMMR'10 Proceedings of the 7th international conference on Exploring music contents
An audio-driven virtual dance-teaching assistant
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Automatic music transcription: challenges and future directions
Journal of Intelligent Information Systems
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The aim of this paper is to propose solutions to some problems that arise in automatic polyphonic transcription of recorded piano music. First, we propose a method that groups spectral information in the frequency-domain and uses a rule-based framework to deal with the known problems of polyphony and harmonicity. Then, we present a novel method for multipitch-estimation that uses both frequency and time-domain information. It assumes signal segments to be the linearly weighted sum of waveforms in a database of individual piano notes. We propose a solution to the problem of generating those waveforms, by using the frequency-domain approach. We show that accurate time-domain transcription can be achieved given an adequate estimation of the database. This suggests an alternative to common frequency-domain approaches that does not require any prior training on a separate database of isolated notes