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Low-rank and sparse subspace modeling of speech for DNN based acoustic modeling

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Low-rank and sparse subspace modeling of speech for DNN based acoustic modeling

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Compressive PCA for Low-Rank Matrices on Graphs

Sparse Hidden Markov Models for Exemplar-based Speech Recognition Using Deep Neural Network Posterior Features

Signal structure: from manifolds to molecules and structured sparsity

Structured Sparsity Models for Reverberant Speech Separation

Compressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

Compressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

Model-Based Compressive Sensing for Multi-Party Distant Speech Recognition

Model-Based Compressive Sensing for Multi-Party Distant Speech Recognition

Model-based Compressive Sensing for Multi-party Distant Speech Recognition

Guaranteed recovery of a low-rank and joint-sparse matrix from incomplete and noisy measurements

Sparse Hidden Markov Models for Exemplar-based Speech Recognition Using Deep Neural Network Posterior Features

Signal structure: from manifolds to molecules and structured sparsity

Compressive PCA for Low-Rank Matrices on Graphs

Compressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

Model-Based Compressive Sensing for Multi-Party Distant Speech Recognition

Model-Based Compressive Sensing for Multi-Party Distant Speech Recognition

Structured Sparsity Models for Reverberant Speech Separation

Compressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

Model-based Compressive Sensing for Multi-party Distant Speech Recognition

Guaranteed recovery of a low-rank and joint-sparse matrix from incomplete and noisy measurements