Search Results for author: Thomas Powers

Found 6 papers, 3 papers with code

Differentiable Greedy Networks

no code implementations30 Oct 2018 Thomas Powers, Rasool Fakoor, Siamak Shakeri, Abhinav Sethy, Amanjit Kainth, Abdel-rahman Mohamed, Ruhi Sarikaya

Optimal selection of a subset of items from a given set is a hard problem that requires combinatorial optimization.

Claim Verification Combinatorial Optimization +1

Deep Recurrent NMF for Speech Separation by Unfolding Iterative Thresholding

1 code implementation21 Sep 2017 Scott Wisdom, Thomas Powers, James Pitton, Les Atlas

This interpretability also provides principled initializations that enable faster training and convergence to better solutions compared to conventional random initialization.

Speech Separation

Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery

1 code implementation22 Nov 2016 Scott Wisdom, Thomas Powers, James Pitton, Les Atlas

Recurrent neural networks (RNNs) are powerful and effective for processing sequential data.

Compressive Sensing

Full-Capacity Unitary Recurrent Neural Networks

2 code implementations NeurIPS 2016 Scott Wisdom, Thomas Powers, John R. Hershey, Jonathan Le Roux, Les Atlas

To address this question, we propose full-capacity uRNNs that optimize their recurrence matrix over all unitary matrices, leading to significantly improved performance over uRNNs that use a restricted-capacity recurrence matrix.

Sequential Image Classification

Enhancement and Recognition of Reverberant and Noisy Speech by Extending Its Coherence

no code implementations2 Sep 2015 Scott Wisdom, Thomas Powers, Les Atlas, James Pitton

Our approach centers around using a single-channel minimum mean-square error log-spectral amplitude (MMSE-LSA) estimator proposed by Habets, which scales coefficients in a time-frequency domain to suppress noise and reverberation.

Automatic Speech Recognition Speech Enhancement +1

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