most citedNeural networks based EEG-Speech Models

26 citations · 64 across the 7 of their papers we have counts for

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cs.SD2016★ 26 cited

Neural networks based EEG-Speech Models

Pengfei Sun, Jun Qin

In this paper, we propose an end-to-end neural network (NN) based EEG-speech (NES) modeling framework, in which three network structures are developed to map imagined EEG signals t…

cs.SD2016★ 5 cited

Enhanced Factored Three-Way Restricted Boltzmann Machines for Speech Detection

Pengfei Sun, Jun Qin

In this letter, we propose enhanced factored three way restricted Boltzmann machines (EFTW-RBMs) for speech detection. The proposed model incorporates conditional feature learning…

cs.SD2016★ 6 cited

Speech Enhancement via Two-Stage Dual Tree Complex Wavelet Packet Transform with a Speech Presence Probability Estimator

Pengfei Sun, Jun Qin

In this paper, a two-stage dual tree complex wavelet packet transform (DTCWPT) based speech enhancement algorithm has been proposed, in which a speech presence probability (SPP) es…

cs.SD2016★ 16 cited

Low Rank and Sparsity Analysis Applied to Speech Enhancement via Online Estimated Dictionary

Pengfei Sun, Jun Qin

We propose an online estimated dictionary based single channel speech enhancement algorithm, which focuses on low rank and sparse matrix decomposition. In this proposed algorithm,…

cs.SD2016

Semi-supervised Speech Enhancement in Envelop and Details Subspaces

Pengfei Sun, Jun Qin

In this study, we propose a modulation decoupling based single channel speech enhancement subspace framework, in which the spectrogram of noisy speech is decoupled as the product o…