Title:
Structured-Sparsity-Models
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Description: To further tackle the ambiguity
of the reflection ratios, we propose a novel formulation of the
reverberation model and estimate the absorption coefficients
through a convex optimization exploiting joint sparsity model
formulated upon spatio-spectral sparsity of concurrent speech
representation. The acoustic parameters are then incorporated
for separating individual speech signals through either structured
sparse recovery or inverse filtering the acoustic channels.
The experiments conducted on real data recordings of spatially
stationary sources demonstrate the effectiveness of the proposed
approach for speech separation and recognition.
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Structured Sparsity Models.pdf
