Frequency-domain blind separation sequencing algorithm of convolutive speech signals
A speech signal and sorting algorithm technology, applied in speech analysis, speech recognition, complex mathematical operations, etc., can solve problems such as order uncertainty, and achieve the effect of good robustness and accuracy
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[0031] What the present invention uses is the convolution aliasing model of K*K (K source signals, K observation signals): Where the observed signal vector x(n)=[x 1 (n),x 2 (n),...,x K (n)] T , source signal vector s(n)=[s 1 (n), s 2 (n), .., s K (n)] T (The superscript "T" means transpose), N is the length of the FIR filter, is the K×K hybrid filter matrix at delay l, where h ij is the impulse response from the jth source signal to the ith sensor. For convolutional blind separation, the goal is to find L K×K separation filter matrices W(l) to estimate the source signal After the formula is short-time Fourier transformed (STFT), the convolutional aliasing model is converted into instantaneous aliasing in each frequency band, that is, in the frequency band f k , there is Y(f k ,τ)=W(f k )X(f k , τ). Through the frequency domain ICA (Independent Component Analysis) algorithm, a K×K separation matrix W(f k ). W(f k ) Each row is an estimated vector of differe...
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