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Monaural Musical Sound Separation Based on Pitch and Common Amplitude Modulation
"... Abstract—Monaural musical sound separation has been extensively studied recently. An important problem in separation of pitched musical sounds is the estimation of time–frequency regions where harmonics overlap. In this paper, we propose a sinusoidal modelingbased separation system that can effecti ..."
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Abstract—Monaural musical sound separation has been extensively studied recently. An important problem in separation of pitched musical sounds is the estimation of time–frequency regions where harmonics overlap. In this paper, we propose a sinusoidal modelingbased separation system that can effectively resolve overlapping harmonics. Our strategy is based on the observations that harmonics of the same source have correlated amplitude envelopes and that the change in phase of a harmonic is related to the instrument’s pitch. We use these two observations in a least squares estimation framework for separation of overlapping harmonics. The system directly distributes mixture energy for harmonics that are unobstructed by other sources. Quantitative evaluation of the proposed system is shown when ground truth pitch information is available, when rough pitch estimates are provided in the form of a MIDI score, and finally, when a multipitch tracking algorithm is used. We also introduce a technique to improve the accuracy of rough pitch estimates. Results show that the proposed system significantly outperforms related monaural musical sound separation systems. Index Terms—Common amplitude modulation (CAM), musical sound separation, sinusoidal modeling, time–frequency masking, underdetermined sound separation. I.
Improving separation of harmonic sources with iterative estimation of spatial cues
 in Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
, 2009
"... Recent work in source separation of twochannel mixtures has used spatial cues (crosschannel amplitude and phase difference coefficients) to estimate timefrequency masks for separating sources. As sources increasingly overlap in the timefrequency domain or the angle between sources decreases, the ..."
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Recent work in source separation of twochannel mixtures has used spatial cues (crosschannel amplitude and phase difference coefficients) to estimate timefrequency masks for separating sources. As sources increasingly overlap in the timefrequency domain or the angle between sources decreases, these spatial cues become unreliable. We introduce a method to reestimate the spatial cues for mixtures of harmonic sources. The newly estimated spatial cues are fed to the system to update each source estimate and the pitch estimate of each source. This iterative procedure is repeated until the difference between the current estimate of the spatial cues and the previous one is under a preset threshold. Results on a set of threesource mixtures of musical instruments show this approach significantly improves separation performance of two existing timefrequency masking systems.
Reconstructing individual monophonic instruments from musical mixtures using scene completion
"... Monaural sound source separation is the process of separating sound sources from a single channel mixture. In mixtures of pitched musical instruments, the problem of overlapping harmonics poses a significant challenge to source separation and reconstruction. One standard method to resolve overlapp ..."
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Monaural sound source separation is the process of separating sound sources from a single channel mixture. In mixtures of pitched musical instruments, the problem of overlapping harmonics poses a significant challenge to source separation and reconstruction. One standard method to resolve overlapped harmonics is based on the assumption that harmonics of the same source have correlated amplitude envelopes: common amplitude modulation (CAM). Based on CAM, overlapped harmonics are approximated using the amplitude envelope from the nonoverlapped harmonics of the same note. CAM assumes nonoverlapped harmonics from the same noteare available and have similar amplitude envelopes to the overlapped harmonics. This is not always the case. A technique is proposed for harmonic temporal envelope estimation based on the idea of scene completion. The system learns the harmonic envelope for each instruments notes from the nonoverlapped harmonics of other notes played by that instrument, wherever they
doi:10.1155/2009/130567 Research Article Musical Sound Separation Based on Binary TimeFrequency Masking
"... The problem of overlapping harmonics is particularly acute in musical sound separation and has not been addressed adequately. We propose a monaural system based on binary timefrequency masking with an emphasis on robust decisions in timefrequency regions, where harmonics from different sources over ..."
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The problem of overlapping harmonics is particularly acute in musical sound separation and has not been addressed adequately. We propose a monaural system based on binary timefrequency masking with an emphasis on robust decisions in timefrequency regions, where harmonics from different sources overlap. Our computational auditory scene analysis system exploits the observation that sounds from the same source tend to have similar spectral envelopes. Quantitative results show that utilizing spectral similarity helps binary decision making in overlapped timefrequency regions and significantly improves separation performance. Copyright © 2009 Y. Li and D. Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
FREQUENCY, PHASE AND AMPLITUDE ESTIMATION OF OVERLAPPING PARTIALS IN MONAURAL MUSICAL SIGNALS
"... ABSTRACT A method is described that simultaneously estimates the frequency, phase and amplitude of two overlapping partials in a monaural musical signal from the amplitudes and phases in three frequency bins of the signal's Odd Discrete Fourier Transform (ODFT). From the transform of the analy ..."
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ABSTRACT A method is described that simultaneously estimates the frequency, phase and amplitude of two overlapping partials in a monaural musical signal from the amplitudes and phases in three frequency bins of the signal's Odd Discrete Fourier Transform (ODFT). From the transform of the analysis window in its analytical form, and given the frequencies of the two partials, an analytical solution for the amplitude and phase of the two overlapping partials was obtained. Furthermore, the frequencies are estimated numerically solving a system of two equations and two unknowns, since no analytical solution could be found. Although the estimation is done independently frame by frame, particular situations (e.g. extremely close frequencies, same phase in the time window) lead to errors, which can be partly corrected with a moving average filter over several time frames. Results are presented for artificial sinusoids with time varying frequencies and amplitudes, and with different levels of noise added. The system still performs well with a SignaltoNoise ratio of down to 30 dB, with moderately modulated frequencies, and time varying amplitudes.