121 citations · 132 across the 6 of their papers we have counts for
6 papers
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition
Wei Zhang, Xiaodong Cui, Ulrich Finkler +6
Modern Automatic Speech Recognition (ASR) systems rely on distributed deep learning to for quick training completion. To enable efficient distributed training, it is imperative tha…
Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition
Khoi-Nguyen C. Mac, Xiaodong Cui, Wei Zhang +1
In automatic speech recognition (ASR), wideband (WB) and narrowband (NB) speech signals with different sampling rates typically use separate acoustic models. Therefore mixed-bandwi…
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition
Xiaodong Cui, Michael Picheny
Evolutionary stochastic gradient descent (ESGD) was proposed as a population-based approach that combines the merits of gradient-aware and gradient-free optimization algorithms for…
Dilated Recurrent Neural Networks
Shiyu Chang, Yang Zhang, Wei Han +7
Learning with recurrent neural networks (RNNs) on long sequences is a notoriously difficult task. There are three major challenges: 1) complex dependencies, 2) vanishing and explod…
Embedding-Based Speaker Adaptive Training of Deep Neural Networks
Xiaodong Cui, Vaibhava Goel, George Saon
An embedding-based speaker adaptive training (SAT) approach is proposed and investigated in this paper for deep neural network acoustic modeling. In this approach, speaker embeddin…
English Conversational Telephone Speech Recognition by Humans and Machines
George Saon, Gakuto Kurata, Tom Sercu +9
One of the most difficult speech recognition tasks is accurate recognition of human to human communication. Advances in deep learning over the last few years have produced major sp…