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In this paper, independent component analysis (ICA) in a subband domain has been extended into a feed-forward network. The feed-forward network maximizes mutual independence of separated current frames using information from the both current and previous multi-channel frames of speech signals captured by a microphone array. To guide into a proper separation preventing permutation and arbitrary scaling,...
In model-based single channel speech separation, factorial hidden Markov models (FHMM) have been successfully applied to model the mixture signal Y(t) = X(t) + V(t) in terms of trained patterns of the speech signals X(t) and V(t). Nonetheless, when the test signals are scaled versions of the trained patterns (i.e. gxX(t) and gvV(t)), the performance of FHMM degrades significantly. In this paper, we...
Blind source extraction (BSE) as desirable for acoustic cocktail party scenarios requires estimates for the target or interfering signals. Conventional single-channel approaches for obtaining the interference estimate rely on noise and interference estimates during absence of the target signal. For multichannel approaches using multiple microphone signals, a separation of simultaneously active target...
In most current model based single channel separation techniques, it is assumed that the recording conditions are identical in the training phase and application phase. In this paper, we consider a general case in which training data and application data have different levels of energy and a technique is proposed to estimate the sources' gains which are required for the separation process. We use...
A new super-resolution algorithm for time delay estimation (TDE) of multipath propagation signals base on least square criterion was proposed. The idea was to decompose the observed data into their signal components and then to estimate the amplitude and time delay of each signal components separately, using cubic slpline interpolation and basing on least square criterion. The algorithm iterated back...
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