Françoise Beaufays
Françoise Beaufays is a Research Scientist at Google, where she leads a team working on on-device machine learning for Speech and Mobile Keyboard models. Her area of scientific expertise covers deep learning, sequence-to-sequence modeling, language modeling and other technologies related to natural language processing, with a recent focus on privacy-preserving modeling techniques. Françoise studied Mechanical and Electrical Engineering in Brussels, Belgium. She holds a PhD in Electrical Engineering and a PhD minor in Italian Literature, both from Stanford University.
Authored Publications
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Google
Handling Compounding in Mobile Keyboard Input
Andreas Christian Kabel
Keith B. Hall
David Rybach
arXiv cs.CL (2022)
Federated Pruning: Improving Neural Network Efficiency with Federated Learning
Rongmei Lin
Yonghui (Yohu) Xiao
Tien-Ju Yang
Ding Zhao
Li Xiong
Giovanni Motta
Interspeech 2022 (2022)
Large-scale ASR Domain Adaptation by Self- and Semi-supervised Learning
David Qiu
Dongseong Hwang
ICASSP (2022) (to appear)
Extracting Targeted Training Data from ASR Models, and How to Mitigate It
Ehsan Amid
Om Thakkar
Proc. Interspeech 2022 (2022) (to appear)
Online Model Compression for Federated Learning with Large Models
Tien-Ju Yang
Yonghui (Yohu) Xiao
Giovanni Motta
(2022)
A Method to Reveal Speaker Identity in Distributed ASR Training,and How to Counter It
Trung Dang
Om Thakkar
Peter Chin
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022, Virtual and Singapore, 23-27 May 2022, {IEEE}, pp. 4338-4342
Revealing and Protecting Labels in Distributed Training
Trung Dang
Om Thakkar
Peter Chin
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, pp. 1727-1738
Training Production Language Models without Memorizing User Data
Om Thakkar
Galen Andrew
(2020)
Understanding Unintended Memorization in Federated Learning
Om Thakkar
Third Workshop on Privacy in Natural Language Processing (PrivateNLP 2021) at 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) (2020)
Federated Learning of N-gram Language Models
Adeline Wong
The SIGNLL Conference on Computational Natural Language Learning (2019)
