9:30, MULT-P2.1
A COMBINED APPROACH OF ARRAY PROCESSING AND INDEPENDENT COMPONENT ANALYSIS FOR BLIND SEPARATION OF ACOUSTIC SIGNALS
F. ASANO, S. EKEDA, M. OGAWA, H. ASOH, N. KITAWAKI
In this paper, two array signal processing techniques are combined with independent component analysis to enhance the performance of blind separation of acoustic signals in a reflective environment such as rooms. The first technique is the subspace method which reduces the effect of room reflection. The second technique is a method of solving permutation, in which coherency of the mixing matrix in adjacent frequencies is utilized.

9:30, MULT-P2.2
BLIND SOURCE SEPARATION COMBINING FREQUENCY-DOMAIN ICA AND BEAMFORMING
H. SARUWATARI, S. KURITA, K. TAKEDA
In this paper, we describe a new method of blind source separation (BSS) on a microphone array combining subband independent component analysis (ICA) and beamforming. The proposed array system consists of the following three sections: (1) subband-ICA-based BSS section with direction-of-arrival (DOA) estimation, (2) null beamforming section based on the estimated DOA information, and (3) integration of (1) and (2) based on the algorithm diversity. Using this technique, we can resolve the low-convergence problem through optimization in ICA. The results of the signal separation experiments reveal that the noise reduction rate (NRR) of about 18dB is obtained under the nonreverberant condition, and NRRs of 8dB and 6dB are obtained in the case that the reverberation times are 150msec and 300msec. These performances are superior to those of both simple ICA-based BSS and simple beamforming method.

9:30, MULT-P2.3
FUNDAMENTAL LIMITATION OF FREQUENCY DOMAIN BLIND SOURCE SEPARATION FOR CONVOLUTIVE MIXTURE OF SPEECH
S. ARAKI, S. MAKINO, T. NISHIKAWA, H. SARUWATARI
Despite several recent proposals to achieve Blind Source Separation (BSS) for realistic acoustic signal, separation performance is still not enough. In particular, when the length of impulse response is long, performance is highly limited. In this paper, we show it is useless to be constrained by the condition, P << T, where T is the frame size of FFT and P is the length of room impulse response. From our experiments, a frame size of 256 and 512 (32 and 64 ms at a sampling frequency of 8 kHz) is best even for the long room reverberation of T_R=150 and 300 ms. We also clarified the reason for poor performance of BSS in long reverberant environment, finding that separation is achieved chiefly for a direct jammer because BSS cannot calculate the inverse of the room transfer function both for the target and jammer signals.

9:30, MULT-P2.4
A SECOND-ORDER DIFFERENTIAL APPROACH FOR UNDERDETERMINED CONVOLUTIVE SOURCE SEPARATION
Y. DEVILLE, S. SAVOLDELLI
This paper concerns the underdetermined case of the convolutive source separation problem, i.e. the situation when the number of observed convolutively mixed signals is lower than the number of sources. We propose a criterion and associated algorithm which, unlike classical approaches, make it possible to perform the separation of a subset of these sources by exploiting their assumed non-stationarity properties. This approach uses the second-order statistics of the signals and adapts the filters of a direct separating system so as to cancel the "differential cross-correlation" of signals derived by this system. This new method is related to the general differential source separation concept that we proposed. Its effectiveness is shown by means of numerical tests.

9:30, MULT-P2.5
BLIND SOURCE SEPARATION OF CONVOLVED SOURCES BY JOINT APPROXIMATE DIAGONALIZATION OF CROSS-SPECTRAL DENSITY MATRICES
K. RAHBAR, J. REILLY
In this paper we present a new method for separating non-stationary sources from their convolutive mixtures based on approximate joint diagonalizing of the observed signals' cross-spectral density matrices. Several blind source separation (BSS) algorithms have been proposed which use approximate joint diagonalization of a set of scalar matrices to estimate the instantaneous mixing matrix. We extend the concept of approximate joint diagonalization to estimate MIMO FIR channels. Based on this estimate we then design a separating network which will recover the original sources up to only a permutation and scaling ambiguity for minimum phase channels. We eliminate the commonly experienced problem of arbitrary scaling and permutation at each frequency bin, by optimizing the cost function directly with respect to the time-domain channel variables. We demonstrate the performance of the algorithm by computer simulations using real speech data. Speech samples are available at: http://sparky.mcmaster.ca/SSP/telephony_kamran.htm.

9:30, MULT-P2.6
BLIND MIMO EQUALIZATION AND JOINT-DIAGONALIZATION CRITERIA
P. COMON, E. MOREAU
We consider the problem of convolutive blind signal separation through the optimization of contrast functions. In this work, we show that some links between contrasts and joint diagonalization criteria can be exhibited in the convolutive case. This allows to devise a constructive algorithm performing MIMO blind equalization, with the help of a joint approximate diagonalization of a set of matrices built from the observations. This analytical algorithm can be run block-wise, which is appropriate in the context of short burst communications.

9:30, MULT-P2.7
ADAPTIVE PARAUNITARY FILTER BANKS FOR CONTRAST-BASED MULTICHANNEL BLIND DECONVOLUTION
X. SUN, S. DOUGLAS
In this paper, we present novel algorithms for multichannel blind deconvolution under output whitening constraints. The algorithms are inspired by recently-developed procedures for gradient adaptive paraunitary filter banks. Several algorithms are developed, including one algorithm that successfully deconvolves mixtures of arbitrary non-zero kurtosis source signals. We provide detailed local stability analyses of the proposed methods to verify their capabilities. Simulations show that the methods successfully deconvolve spatio-temporal mixtures of statistically-independent source signals.

9:30, MULT-P2.8
A MULTIRESOLUTION APPROACH TO BLIND SEPARATION OF SPEECH SIGNALS IN A REVERBERANT ENVIRONMENT
M. IKRAM, D. MORGAN
The performance of existing blind speech separation methods is limited in a realistic reverberant environment, where a need for long un-mixing filters is imperative. We first show how these methods suffer while trying to balance the competing objectives of frequency-domain permutation alignment and spectral resolution. We then propose a multistage multiresolution algorithm, which aligns the un-mixing filter permutations over the whole frequency band without sacrificing spectral resolution. We perform experiments in both real and simulated reverberant environments, and obtain improved separation results that are comparable to the ideal benchmark obtained by aligning the permutations using prior knowledge of the mixing filters.

9:30, MULT-P2.9
FREQUENCY DOMAIN MULTI-CHANNEL SPEECH SEPARATION AND ITS APPLICATIONS
M. HANDA, T. NAGAI, A. KUREMATSU
In this paper, a multi-channel speech separation method for real environments is proposed. The proposed method is based on frequency assignment, namely the magnitude of each channel at the same frequency bin is compared with each other and it is assigned to the channel, to which it originally belongs. This method is a direct consequence of frequency domain interpretation of the eigendecomposition method proposed by Cao et al.. Furthermore, our proposed method does not require eigendecomposition, which consumes the costs of computation. We also present two example applications of the proposed method, that is, voice controlled computers in a multi-user environment and a noise removal in cellular phone using two microphones.

9:30, MULT-P2.10
FREQUENCY-DOMAIN CONTRAST FUNCTIONS FOR SEPARATION OF CONVOLUTIVE MIXTURES
J. PESQUET, B. CHEN, A. PETROPULU
This paper addresses the problem of blind separation of convolutive mixtures via contrast maximization. New frequency domain contrast functions are constructed based on second and higher-order spectra of the observations. They allow to separate mixtures of sources which are spatially independent, and temporally possibly non i.i.d. or non-linear processes. The proposed criteria provide a framework for extending to the convolutive case contrasts that have been proposed in the context of instantaneous mixtures.