Convolutive blind separation of speech mixtures using the natural gradient
Speech Communication - Special issue on speech processing for hearing aids
Adaptive blind separation with an unknown number of sources
Neural Computation
Sound onset detection by applying psychoacoustic knowledge
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
First stereo audio source separation evaluation campaign: data, algorithms and results
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
A frequency domain blind signal separation method based ondecorrelation
IEEE Transactions on Signal Processing
Musical source separation using time-frequency source priors
IEEE Transactions on Audio, Speech, and Language Processing
Audio source separation with a single sensor
IEEE Transactions on Audio, Speech, and Language Processing
| Hi-index | 0.00 |
We present a sequence of empirical methods to determine the number of sources in musical signals when only one channel is available. Rather than building evidence through a statistical model-based approach, we instead develop a carefully tuned and tested two-stage system that is able to function effectively even in extremely underdetermined conditions. A first, more general procedure accurately determines the number of sources that are not closely harmonically related, while the second stage subsequently detects the presence of any remaining sources. The main advantages of this approach lie in its avoidance of the restrictive assumptions that can accompany more complex models in underdetermined cases, and in its use of robust heuristics to identify and exploit as much source-specific information as possible. These features make it possible to address even the most difficult cases in which sources are closely harmonically related, or even share the same fundamental frequency. We report an overall accuracy of nearly 80% on average, using both random and harmonically related mixtures of one to six sources taken from two widely available musical instrument databases--a notable result that demonstrates both the efficiency and the robustness of our proposed procedure.