303 citations · 381 across the 12 of their papers we have counts for
4 papers · 1 filter
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition
Chao-Han Huck Yang, Jun Qi, Sabato Marco Siniscalchi +1
We propose an ensemble learning framework with Poisson sub-sampling to effectively train a collection of teacher models to issue some differential privacy (DP) guarantee for traini…
On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression
Jun Qi, Jun Du, Sabato Marco Siniscalchi +2
In this paper, we exploit the properties of mean absolute error (MAE) as a loss function for the deep neural network (DNN) based vector-to-vector regression. The goal of this work…
Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement
Jun Qi, Hu Hu, Yannan Wang +3
This paper investigates different trade-offs between the number of model parameters and enhanced speech qualities by employing several deep tensor-to-vector regression models for s…
Tensor-to-Vector Regression for Multi-channel Speech Enhancement based on Tensor-Train Network
Jun Qi, Hu Hu, Yannan Wang +3
We propose a tensor-to-vector regression approach to multi-channel speech enhancement in order to address the issue of input size explosion and hidden-layer size expansion. The key…