-
Improving Streaming Automatic Speech Recognition With Non-Streaming Model Distillation On Unsupervised Data
Streaming end-to-end automatic speech recognition (ASR) models are widel...
10/22/2020 ∙ by Thibault Doutre, et al. ∙
0
∙
share
read it
-
Uncertainty Estimation with Infinitesimal Jackknife, Its Distribution and Mean-Field Approximation
Uncertainty quantification is an important research area in machine lear...
06/13/2020 ∙ by Zhiyun Lu, et al. ∙
31
∙
share
read it
-
Speech Sentiment Analysis via Pre-trained Features from End-to-end ASR Models
In this paper, we propose to use pre-trained features from end-to-end AS...
11/21/2019 ∙ by Zhiyun Lu, et al. ∙
0
∙
share
read it
-
Hyper-parameter Tuning under a Budget Constraint
We study a budgeted hyper-parameter tuning problem, where we optimize th...
02/01/2019 ∙ by Zhiyun Lu, et al. ∙
16
∙
share
read it
-
Kernel Approximation Methods for Speech Recognition
We study large-scale kernel methods for acoustic modeling in speech reco...
01/13/2017 ∙ by Avner May, et al. ∙
0
∙
share
read it
-
Learning Compact Recurrent Neural Networks
Recurrent neural networks (RNNs), including long short-term memory (LSTM...
04/09/2016 ∙ by Zhiyun Lu, et al. ∙
0
∙
share
read it
-
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
We study large-scale kernel methods for acoustic modeling and compare to...
03/18/2016 ∙ by Zhiyun Lu, et al. ∙
0
∙
share
read it
-
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
The computational complexity of kernel methods has often been a major ba...
11/14/2014 ∙ by Zhiyun Lu, et al. ∙
0
∙
share
read it
