World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
12720
World Ranking
9060
National Ranking
3850

Francoise Beaufays publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Francoise Beaufays sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 126 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Francoise Beaufays D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Francoise Beaufays sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Francoise Beaufays is affiliated with Google in the United States. Their research primarily centers on computer science, with a strong focus on artificial intelligence and signal processing.

Their publication record includes significant contributions to speech recognition and related areas. The main topics covered in their work are:

  • Speech Recognition and Synthesis
  • Speech and Audio Processing
  • Music and Audio Processing
  • Privacy-Preserving Technologies in Data
  • Topic Modeling
  • Speech and dialogue systems
  • Natural Language Processing Techniques

Beaufays has published extensively across several venues, notably:

  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • IEEE Journal of Selected Topics in Signal Processing

Recent papers authored or co-authored by Beaufays encompass:

  • "BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition" (2022) IEEE Journal of Selected Topics in Signal Processing
  • "Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages" (2023) arXiv (Cornell University)
  • "Large-Scale ASR Domain Adaptation Using Self- and Semi-Supervised Learning" (2022) ICASSP 2022
  • "Fast Contextual Adaptation with Neural Associative Memory for On-Device Personalized Speech Recognition" (2022) ICASSP 2022
  • "Understanding Unintended Memorization in Federated Learning" (2020) arXiv (Cornell University)

Frequent co-authors in Beaufays's research network include:

  • Khe Chai Sim
  • Giovanni Motta
  • Rajiv Mathews
  • Trevor Strohman
  • Tien-Ju Yang

Beaufays's work engages deeply with the development and scaling of automatic speech recognition systems, including domain adaptation methods and privacy considerations in federated learning. Their research also extends to contextual adaptation techniques and multilingual speech recognition frameworks.

Best Publications

  • Long Short-Term Memory Recurrent Neural Network Architectures for Large Scale Acoustic Modeling

    Hasim Sak;Andrew W. Senior;Françoise Beaufays

  • Federated Learning for Mobile Keyboard Prediction

    Andrew Hard;Chloé M Kiddon;Daniel Ramage;Francoise Beaufays

  • Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition

    Hasim Sak;Andrew W. Senior;Françoise Beaufays

  • Applied Federated Learning: Improving Google Keyboard Query Suggestions

    Timothy Yang;Galen Andrew;Hubert Eichner;Haicheng Sun

  • Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition

    Hasim Sak;Andrew W. Senior;Kanishka Rao;Françoise Beaufays

  • “Your Word is my Command”: Google Search by Voice: A Case Study

    Johan Schalkwyk;Doug Beeferman;Françoise Beaufays;Bill Byrne

  • Business listing search

    Brian Strope;William J. Byrne;Francoise Beaufays

  • Transform-domain adaptive filters: an analytical approach

    F. Beaufays

  • Speech Recognition with Parallel Recognition Tasks

    Brian Patrick Strope;Francoise Beaufays;Olivier Siohan

  • Integrating voice-enabled local search and contact lists

    Francoise Beaufays;Brian Strope;William J. Byrne

  • Application of neural networks to load-frequency control in power systems

    Françoise Beaufays;Youssef Abdel-Magid;Bernard Widrow

  • Grapheme-to-phoneme conversion using Long Short-Term Memory recurrent neural networks

    Kanishka Rao;Fuchun Peng;Hasim Sak;Francoise Beaufays

  • Learning acoustic frame labeling for speech recognition with recurrent neural networks

    Hasim Sak;Andrew Senior;Kanishka Rao;Ozan Irsoy

  • Personalized speech recognition on mobile devices

    Ian McGraw;Rohit Prabhavalkar;Raziel Alvarez;Montse Gonzalez Arenas

  • Neural-network based measures of confidence for word recognition

    M. Weintraub;F. Beaufays;Z. Rivlin;Y. Konig

  • Method and system for learning linguistically valid word pronunciations from acoustic data

    Francoise Beaufays;Ananth Sankar;Mitchel Weintraub;Shaun Williams

  • Robust text-independent speaker identification over telephone channels

    H.A. Murthy;F. Beaufays;L.P. Heck;M. Weintraub

  • BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

    Yu Zhang;Daniel S. Park;Wei Han;James Qin

  • Data driven pronunciation learning with crowd sourcing

    Fuchun Peng;Francoise Beaufays;Brian Strope;Xin Lei

  • Recurrent Neural Aligner: An Encoder-Decoder Neural Network Model for Sequence to Sequence Mapping.

    Haşim Sak;Matt Shannon;Kanishka Rao;Françoise Beaufays

  • Federated Evaluation of On-device Personalization

    Chloé M Kiddon;Daniel R Ramage;Françoise Simone Beaufays;Hubert Eichner

  • Federated Learning Of Out-Of-Vocabulary Words

    Francoise Beaufays;Rajiv Mathews

Frequent Co-Authors

Hasim Sak
Hasim Sak Google (United States)
Eric A. Wan
Eric A. Wan Portland State University
Andrew W. Senior
Andrew W. Senior Google (United States)
Bernard Widrow
Bernard Widrow Stanford University
Michael Riley
Michael Riley Google (United States)
Michiel Bacchiani
Michiel Bacchiani Google (United States)
Daniel Ramage
Daniel Ramage Google (United States)
Jakob Foerster
Jakob Foerster University of Oxford
Thomas M. Breuel
Thomas M. Breuel Nvidia (United States)
Tara N. Sainath
Tara N. Sainath Google (United States)

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