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Subject = Source Separation;
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Displaying Results 1  5 of 5 on page 1 of 1
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Constructing TimeFrequency Dictionaries for Source Separation via TimeFrequency Masking and Source Localisation
(2004)
de Fréin, Ruairí; Rickard, Scott T.; Pearlmutter, Barak A.
Constructing TimeFrequency Dictionaries for Source Separation via TimeFrequency Masking and Source Localisation
(2004)
de Fréin, Ruairí; Rickard, Scott T.; Pearlmutter, Barak A.
Abstract:
We describe a new localisation and source separation algorithm which is based upon the accurate construction of timefrequency spatial signatures. We present a technique for constructing timefrequency spatial signatures with the required accuracy. This algorithm for multichannel source separation and localisation allows arbitrary placement of microphones yet achieves good performance. We demonstrate the efficacy of the technique using source location estimates and compare estimated timefrequency masks with the ideal 0 dB mask.
http://mural.maynoothuniversity.ie/8118/
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Drum Source Separation using Percussive Feature Detection and Spectral Modulation
(2005)
Barry, Dan; Fitzgerald, Derry; Coyle, Eugene; Lawlor, Bob
Drum Source Separation using Percussive Feature Detection and Spectral Modulation
(2005)
Barry, Dan; Fitzgerald, Derry; Coyle, Eugene; Lawlor, Bob
Abstract:
We present a method for the separation and resynthesis of drum sources from single channel polyphonic mixtures. The frequency domain technique involves identifying the presence of a drum using a novel percussive feature detection function, after which the shorttime magnitude spectrum is estimated and scaled according to an estimated timeamplitude function derived from the percussive measure. In addition to producing high quality separation results, the method we describe is also a useful preprocess for drum transcription techniques such as Prior Subspace Analysis in the presence of pitched instruments.
http://mural.maynoothuniversity.ie/699/
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Linear Program Differentiation For SingleCHannel Speech Separation
(2005)
Pearlmutter, Barak A.; Olsson, Rasmus K.
Linear Program Differentiation For SingleCHannel Speech Separation
(2005)
Pearlmutter, Barak A.; Olsson, Rasmus K.
Abstract:
Many apparently difficult problems can be solved by reduction to linear programming. Such problems are often subproblems within larger systems. When gradient optimisation of the entire larger system is desired, it is necessary to propagate gradients through the internallyinvoked LP solver. For instance, when an intermediate quantity z is the solution to a linear program involving constraint matrix A, a vector of sensitivities dE/dz will induce sensitivities dE/dA. Here we show how these can be efficiently calculated, when they exist. This allows algorithmic differentiation to be applied to algorithms that invoke linear programming solvers as subroutines, as is common when using sparse representations in signal processing. Here we apply it to gradient optimisation of overcomplete dictionaries for maximally sparse representations of a speech corpus. The dictionaries are employed in a singlechannel speech separation task, leading to 5 dB and 8 dB targettointerference ratio improvem...
http://mural.maynoothuniversity.ie/565/
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Realtime Sound Source Separation: Azimuth Discrimination and Resynthesis
(2003)
Barry, Dan; Lawlor, Bob; Coyle, Eugene
Realtime Sound Source Separation: Azimuth Discrimination and Resynthesis
(2003)
Barry, Dan; Lawlor, Bob; Coyle, Eugene
Abstract:
We present a realtime sound source separation algorithm which performs the task of source separation based on the lateral displacement of a source within the stereo field. The algorithm exploits the use of the pan pot as a means to achieve image localisation within stereophonic recordings. As such, only an interaural intensity difference exists between left and right channels for a single source. Gain scaling and phase cancellation techniques are used in the frequency domain to expose frequency dependent nulls across the azimuth plane. The position of these nulls in conjunction with magnitude estimation and grouping techniques are then used to resynthesise separated sources. Results obtained from real recordings show that for music, this algorithm outperforms current source separation schemes.
http://mural.maynoothuniversity.ie/9761/
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Second Order Blind Source Separation By Recursive Splitting Of Signal Subspaces
(2000)
Zibulevsky, Michael; Pearlmutter, Barak A.
Second Order Blind Source Separation By Recursive Splitting Of Signal Subspaces
(2000)
Zibulevsky, Michael; Pearlmutter, Barak A.
Abstract:
We present an approach to blind source separation based on delayed correlations. This method recursively splits separation space into subspaces spanned by groups of sources. The inner loop consists of repeated application of a standard eigenvalue decomposition. When the number of sources is large this algorithm is significantly faster than joint diagonalization of crosscovariance matrices.
http://mural.maynoothuniversity.ie/8124/
Displaying Results 1  5 of 5 on page 1 of 1
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2005 (2)
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