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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...
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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...
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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...
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Hyper-parameter Tuning under a Budget Constraint
We study a budgeted hyper-parameter tuning problem, where we optimize th...
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Kernel Approximation Methods for Speech Recognition
We study large-scale kernel methods for acoustic modeling in speech reco...
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Learning Compact Recurrent Neural Networks
Recurrent neural networks (RNNs), including long short-term memory (LSTM...
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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...
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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...
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