EURASIP Journal on Audio, Speech, and Music Processing
Monaural musical sound separation based on pitch and common amplitude modulation
IEEE Transactions on Audio, Speech, and Language Processing
Adaptive harmonic spectral decomposition for multiple pitch estimation
IEEE Transactions on Audio, Speech, and Language Processing
Correlation-based amplitude estimation of coincident partials in monaural musical signals
EURASIP Journal on Audio, Speech, and Music Processing
Single channel music sound separation based on spectrogram decomposition and note classification
CMMR'10 Proceedings of the 7th international conference on Exploring music contents
Single-Channel mixture decomposition using bayesian harmonic models
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Wavelet ridges for musical instrument classification
Journal of Intelligent Information Systems
Multiple instrument mixtures source separation evaluation using instrument-dependent NMF models
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Improved music similarity computation based on tone objects
Proceedings of the 7th Audio Mostly Conference: A Conference on Interaction with Sound
| Hi-index | 0.00 |
This paper discusses the separation of two or more simultaneously excited pitched notes from a mono sound file into separate tracks. In fact, this is an intermediate stage in the longer-term goal of separating out at least two interweaving melodies of different sound sources from a mono file. The approach is essentially to filter the set of harmonics of each note from the mixed spectrum in each time frame of audio. A major consideration has been the separation of overlapping harmonics, and three filter designs are proposed for splitting a spectral peak into its constituent partials given the rough frequency and amplitude estimates of each partial contained within. The overall quality of separation has been good for mixes of up to seven orchestral notes and has been confirmed by measured average signal-to-residual ratios of around 10-20 dB