Separation of harmonic sound sources using sinusoidal modeling
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Multipitch estimation and sound separation by the spectral smoothness principle
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
A generative model for music transcription
IEEE Transactions on Audio, Speech, and Language Processing
Melody Transcription From Music Audio: Approaches and Evaluation
IEEE Transactions on Audio, Speech, and Language Processing
Melody Extraction and Musical Onset Detection via Probabilistic Models of Framewise STFT Peak Data
IEEE Transactions on Audio, Speech, and Language Processing
Automatic Piano Transcription Using Frequency and Time-Domain Information
IEEE Transactions on Audio, Speech, and Language Processing
Unsupervised analysis of polyphonic music by sparse coding
IEEE Transactions on Neural Networks
Polyphonic music separation based on the simplified energy splitter
WSEAS Transactions on Signal Processing
Simple and powerful instrument model for the source separation of polyphonic music
WSEAS Transactions on Signal Processing
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A polyphonic musical recording is the superposition of many separate tracks which are downmixed to fewer channels. Decomposition of such a signal to separate instrument tracks or notes has always been a challenge. It is theoretically impossible to extract the component tracks without the information that was lost at the superposition. In this paper a new way of sound separation of mono-aural digital recordings is proposed where lost information is recovered by using a model of real instruments in order to make the separation of individual musical notes possible.