A TIC-MRF approach to speaker clustering on i-vectors yields relative DER reductions of 43.22% on CRSS-PLTL and 29.37%/9.21% on two AMI meetings versus cosine K-means and movMF baselines.
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State-space subspace techniques recover network topology from partial input-output data of continuous-time linear systems, with a convergent alternating-projections algorithm.
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Toeplitz Inverse Covariance based Robust Speaker Clustering for Naturalistic Audio Streams
A TIC-MRF approach to speaker clustering on i-vectors yields relative DER reductions of 43.22% on CRSS-PLTL and 29.37%/9.21% on two AMI meetings versus cosine K-means and movMF baselines.
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State-Space Network Topology Identification from Partial Observations
State-space subspace techniques recover network topology from partial input-output data of continuous-time linear systems, with a convergent alternating-projections algorithm.