Title | ||
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Partial separation method for solving permutation problem in frequency domain blind source separation of speech signals |
Abstract | ||
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This paper addresses the well known permutation problem in frequency domain blind source separation. The proposed method uses correlation between two signals in each DFT bin to solve the permutation problem. One of the signals is partially separated by a time domain blind source separation method and the other is obtained by the frequency domain blind source separation method. Two different ways of configuring the time and frequency domain blocks, i.e., in parallel or cascade, have been studied. The cascaded configuration not only achieves a better separation performance but also reduces the computational cost as compared to the parallel configuration. |
Year | DOI | Venue |
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2008 | 10.1016/j.neucom.2007.08.030 | Neurocomputing |
Keywords | Field | DocType |
better separation performance,separation method,speech signal,partial separation method,cascaded configuration,time domain blind source,frequency domain block,frequency domain blind source,parallel configuration,dft bin,permutation problem,direction of arrival,frequency domain,independent component analysis,time domain,blind source separation | Time domain,Frequency domain,Bin,Direction of arrival,Computer science,Permutation,Artificial intelligence,Independent component analysis,Cascade,Blind signal separation,Machine learning | Journal |
Volume | Issue | ISSN |
71 | 10-12 | Neurocomputing |
Citations | PageRank | References |
3 | 0.41 | 16 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
V. G. Reju | 1 | 76 | 6.06 |
Soo Ngee Koh | 2 | 314 | 39.76 |
Ing Yann Soon | 3 | 346 | 29.94 |