World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
15047
World Ranking
4726
National Ranking
2198

John R. Hershey 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 John R. Hershey 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: 177 publications — 37th percentile

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

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

John R. Hershey 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 John R. Hershey 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

John R. Hershey is a researcher affiliated with Google in the United States, specializing in computer science with a focus on signal processing and artificial intelligence. Their body of work primarily addresses topics related to speech and audio processing, speech recognition and synthesis, and music and audio processing.

Their research contributions encompass a variety of topics, including:

  • Speech and Audio Processing
  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Hearing Loss and Rehabilitation
  • Advanced Adaptive Filtering Techniques
  • Phonetics and Phonology Research
  • Animal Vocal Communication and Behavior

Hershey has published extensively in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • OPAL (Open@LaTrobe) (La Trobe University)

Among their recent publications are:

  • Unsupervised Sound Separation Using Mixture Invariant Training, 2020, arXiv (Cornell University)
  • Improving Bird Classification with Unsupervised Sound Separation, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes, 2020, arXiv (Cornell University)
  • Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds, 2020, arXiv (Cornell University)
  • Distance-Based Sound Separation, 2022, Interspeech 2022

Hershey has collaborated frequently with several researchers, including:

  • Scott Wisdom
  • Hakan Erdoğan
  • Efthymios Tzinis
  • Shinji Watanabe
  • Nicolas Turpault

Their research predominantly falls within the main field of computer science, with significant contributions to signal processing and artificial intelligence. The subfields also include cognitive neuroscience, computational mechanics, and computer vision and pattern recognition.

Best Publications

  • Deep clustering: Discriminative embeddings for segmentation and separation

    John R. Hershey;Zhuo Chen;Jonathan Le Roux;Shinji Watanabe

  • Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models

    J. R. Hershey;P. A. Olsen

  • SDR – Half-baked or Well Done?

    Jonathan Le Roux;Scott Wisdom;Hakan Erdogan;John R. Hershey

  • Hybrid CTC/Attention Architecture for End-to-End Speech Recognition

    Shinji Watanabe;Takaaki Hori;Suyoun Kim;John R. Hershey

  • Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks

    Hakan Erdogan;John R. Hershey;Shinji Watanabe;Jonathan Le Roux

  • Speech Enhancement with LSTM Recurrent Neural Networks and its Application to Noise-Robust ASR

    Felix Weninger;Hakan Erdogan;Shinji Watanabe;Emmanuel Vincent

  • Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures

    John R. Hershey;Jonathan Le Roux;Felix Weninger

  • Attention-Based Multimodal Fusion for Video Description

    Chiori Hori;Takaaki Hori;Teng-Yok Lee;Ziming Zhang

  • Single-Channel Multi-Speaker Separation using Deep Clustering

    Yusuf Ziya Isik;Yusuf Ziya Isik;Jonathan Le Roux;Zhuo Chen;Zhuo Chen;Shinji Watanabe

  • VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking

    Hannah Raphaelle Muckenhirn;Ignacio Lopez Moreno;John Hershey;Kevin Wilson

  • Audio Vision: Using Audio-Visual Synchrony to Locate Sounds

    John R. Hershey;Javier R. Movellan

  • Improved MVDR beamforming using single-channel mask prediction networks

    Hakan Erdogan;John R. Hershey;Shinji Watanabe;Michael I. Mandel

  • Discriminatively trained recurrent neural networks for single-channel speech separation

    Felix Weninger;John R. Hershey;Jonathan Le Roux;Bjorn Schuller

  • Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation

    Zhong-Qiu Wang;Jonathan Le Roux;John R. Hershey

  • Full-capacity unitary recurrent neural networks

    Scott Wisdom;Thomas Powers;John R. Hershey;Jonathan Le Roux

  • Monaural speech separation and recognition challenge

    Martin Cooke;John R. Hershey;Steven J. Rennie

  • Super-human multi-talker speech recognition: A graphical modeling approach

    John R. Hershey;Steven J. Rennie;Peder A. Olsen;Trausti T. Kristjansson

  • Deep beamforming networks for multi-channel speech recognition

    Xiong Xiao;Shinji Watanabe;Hakan Erdogan;Liang Lu

  • Alternative Objective Functions for Deep Clustering

    Zhong-Qiu Wang;Jonathan Le Roux;John R. Hershey

  • Deep clustering and conventional networks for music separation: Stronger together

    Yi Luo;Zhuo Chen;John R. Hershey;Jonathan Le Roux

Frequent Co-Authors

Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Jonathan Le Roux
Jonathan Le Roux Mitsubishi Electric (United States)
Hakan Erdogan
Hakan Erdogan Google (United States)
Zhong-Qiu Wang
Zhong-Qiu Wang Southern University of Science and Technology
Felix Weninger
Felix Weninger Nuance Communications (United States)
Daniel P. W. Ellis
Daniel P. W. Ellis Google (United States)
Justin Salamon
Justin Salamon Adobe Systems (United States)
Javier R. Movellan
Javier R. Movellan University of California, San Diego
Aren Jansen
Aren Jansen Google (United States)

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