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Online Similarity-and-Independence-Aware Beamformer for Low-latency Target Sound Extraction
Thus, experiments using the CHiME-3 dataset confirm that 1) the online algorithm reduces latency; 2) SWF-based scaling eliminates the gap between the two algorithms while improving the accuracy; 3) TV GG model achieves the best accuracy when it corresponds to the Laplacian model; and 4) our online SIBF outperforms the conventional linear TSE, including the minimum mean square error beamformer.
Is the Ideal Ratio Mask Really the Best? -- Exploring the Best Extraction Performance and Optimal Mask of Mask-based Beamformers
Via the experiments with the CHiME-3 dataset, we verify that the four BFs have the same peak performance as the upper bound provided by the ideal MWF BF, whereas the optimal mask depends on the adopted BF and differs from the IRM.
Similarity-and-Independence-Aware Beamformer with Iterative Casting and Boost Start for Target Source Extraction Using Reference
This study describes a method for target source extraction, called the similarity-and-independence-aware beamformer (SIBF).
Similarity-and-Independence-Aware Beamformer: Method for Target Source Extraction using Magnitude Spectrogram as Reference
Index Terms: semiblind source separation, similarity-and-independence-aware beamformer, deflationary independent component analysis, source model
