Convexity and Fast Speech Extraction by Split Bregman Method

作者: Jack Xin , Wenye Ma , Meng Yu , Stanley J. Osher

DOI:

关键词: ConvexityArtificial intelligenceRegularization (mathematics)Source separationConvex optimizationPattern recognitionComputer scienceBregman methodExtraction (chemistry)

摘要: A fast speech extraction (FSE) method is presented using convex optimization made possible by pause detection of the sources. Sparse unmixing filters are sought l1 regularization and split Bregman method. subdivided developed for efficiently estimating long reverberations in real room recordings. The based on a binary mask source separation FSE evaluated found to outperform existing blind approaches both synthetic recorded data terms overall computational speed quality. Index Terms: convexity, sparse filters, method, extraction.

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