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Efficient Knowledge Distillation for RNN-Transducer Models
Knowledge Distillation is an effective method of transferring knowledge ...
11/11/2020 ∙ by Sankaran Panchapagesan, et al. ∙
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Towards NNGP-guided Neural Architecture Search
The predictions of wide Bayesian neural networks are described by a Gaus...
11/11/2020 ∙ by Daniel S. Park, et al. ∙
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Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition
We employ a combination of recent developments in semi-supervised learni...
10/20/2020 ∙ by Yu Zhang, et al. ∙
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Improved Noisy Student Training for Automatic Speech Recognition
Recently, a semi-supervised learning method known as "noisy student trai...
05/19/2020 ∙ by Daniel S. Park, et al. ∙
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SpecAugment on Large Scale Datasets
Recently, SpecAugment, an augmentation scheme for automatic speech recog...
12/11/2019 ∙ by Daniel S. Park, et al. ∙
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The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study
We investigate how the final parameters found by stochastic gradient des...
05/09/2019 ∙ by Daniel S. Park, et al. ∙
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SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
We present SpecAugment, a simple data augmentation method for speech rec...
04/18/2019 ∙ by Daniel S. Park, et al. ∙
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