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10/04/2022
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints
All state-of-the-art (SOTA) differentially private machine learning (DP ...
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08/05/2022
Large vocabulary speech recognition for languages of Africa: multilingual modeling and self-supervised learning
Almost none of the 2,000+ languages spoken in Africa have widely availab...
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07/02/2022
UserLibri: A Dataset for ASR Personalization Using Only Text
Personalization of speech models on mobile devices (on-device personaliz...
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05/26/2022
Mixed Federated Learning: Joint Decentralized and Centralized Learning
Federated learning (FL) enables learning from decentralized privacy-sens...
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05/06/2022
Online Model Compression for Federated Learning with Large Models
This paper addresses the challenges of training large neural network mod...
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04/20/2022
Detecting Unintended Memorization in Language-Model-Fused ASR
End-to-end (E2E) models are often being accompanied by language models (...
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04/18/2022
Extracting Targeted Training Data from ASR Models, and How to Mitigate It
Recent work has designed methods to demonstrate that model updates in AS...
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04/11/2022
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training
We trained a keyword spotting model using federated learning on real use...
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11/23/2021
Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift
With privacy as a motivation, Federated Learning (FL) is an increasingly...
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10/31/2021
Revealing and Protecting Labels in Distributed Training
Distributed learning paradigms such as federated learning often involve ...
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04/15/2021
A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter It
End-to-end Automatic Speech Recognition (ASR) models are commonly traine...
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04/06/2021
Communication-Efficient Agnostic Federated Averaging
In distributed learning settings such as federated learning, the trainin...
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09/21/2020
Training Production Language Models without Memorizing User Data
This paper presents the first consumer-scale next-word prediction (NWP) ...
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06/12/2020
Understanding Unintended Memorization in Federated Learning
Recent works have shown that generative sequence models (e.g., language ...
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05/21/2020
Training Keyword Spotting Models on Non-IID Data with Federated Learning
We demonstrate that a production-quality keyword-spotting model can be t...
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11/15/2019
Generative Models for Effective ML on Private, Decentralized Datasets
To improve real-world applications of machine learning, experienced mode...
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10/22/2019
Federated Evaluation of On-device Personalization
Federated learning is a distributed, on-device computation framework tha...
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10/08/2019
Federated Learning of N-gram Language Models
We propose algorithms to train production-quality n-gram language models...
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06/11/2019
Federated Learning for Emoji Prediction in a Mobile Keyboard
We show that a word-level recurrent neural network can predict emoji fro...
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03/26/2019
Federated Learning Of Out-Of-Vocabulary Words
We demonstrate that a character-level recurrent neural network is able t...
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11/08/2018