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Exploring Targeted Universal Adversarial Perturbations to End-to-end ASR Models
Although end-to-end automatic speech recognition (e2e ASR) models are wi...
04/06/2021 ∙ by Zhiyun Lu, et al. ∙
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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. ∙
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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. ∙
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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. ∙
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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. ∙
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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. ∙
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Learning Compact Recurrent Neural Networks
Recurrent neural networks (RNNs), including long short-term memory (LSTM...
04/09/2016 ∙ by Zhiyun Lu, et al. ∙
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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. ∙
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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. ∙
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