The proposed SCA-based approach has two main stages: modal matrix estimation and modal displacement estimation.
In addition, we provide an analysis of the computational complexity associated with the i-vector and i-supervector at four different stages: loading matrix estimation, i-vector and i-supervector extraction, PLDA model training, and verification score calculation.
Furthermore, we analyzed the computational complexity of the i-supervector system, compared to that of the i-vector, at four different stages, namely, loading matrix estimation, posterior extraction, PLDA modeling, and PLDA scoring.
Furthermore, we also analyze the computational complexity of the i-supervector system, compared with that of the i-vector, at four different stages of loading matrix estimation, posterior extraction, PLDA modeling, and PLDA scoring.
We compared the total time and the real-time factor of i-supervector and i-vector systems at four different stages, namely, loading matrix estimation, posterior extraction, PLDA modeling, and PLDA scoring.
In the activity estimation stage, a source spectral exemplar matrix X s is decomposed into a linear combination of bases from the source dictionary A s.
The PCA matrix is calculated using 10 000 samples in the initial channel estimation stage.
The filtering of the activation matrix by H A, done in step 3 of the NMF update algorithm, is motivated by the need to remove traces of reverberation that remain in matrix A. These traces are caused by imperfections in the initial estimation stage and by the first stage of NMF reconstruction before the filter update is applied (step 2 and Fig. 3).
If separate estimations of the multi-relay channels Hrd, Hrr, and Hsr are required, for instance, to optimize the source precoding matrix and the relays' AF matrices, three separate LS estimation stages should operate sequentially at the destination.
Panning matrix estimation and NMF-based separation are described in detail, explaining how the output of an automatic music transcription stage is used to discriminate single-source time-frequency zones.
