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07/31/2023
Discovering Adaptable Symbolic Algorithms from Scratch
Autonomous robots deployed in the real world will need control policies ...
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03/02/2023
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
We introduce the Universal Speech Model (USM), a single large model that...
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02/08/2023
Noise2Music: Text-conditioned Music Generation with Diffusion Models
We introduce Noise2Music, where a series of diffusion models is trained ...
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10/19/2022
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR
Data augmentation is a ubiquitous technique used to provide robustness t...
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09/27/2021
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition
We summarize the results of a host of efforts using giant automatic spee...
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11/11/2020
Efficient Knowledge Distillation for RNN-Transducer Models
Knowledge Distillation is an effective method of transferring knowledge ...
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11/11/2020
Towards NNGP-guided Neural Architecture Search
The predictions of wide Bayesian neural networks are described by a Gaus...
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10/20/2020
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition
We employ a combination of recent developments in semi-supervised learni...
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05/19/2020
Improved Noisy Student Training for Automatic Speech Recognition
Recently, a semi-supervised learning method known as "noisy student trai...
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12/11/2019
SpecAugment on Large Scale Datasets
Recently, SpecAugment, an augmentation scheme for automatic speech recog...
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05/09/2019
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...
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04/18/2019