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D-Index & Metrics

Computer Science

D-Index
50
Citations
14373
World Ranking
5504
National Ranking
328

Sharon Goldwater 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 Sharon Goldwater 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: 161 publications — 31st percentile

31% of scientists in this discipline score the same or lower.

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

Sharon Goldwater 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 Sharon Goldwater 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Sharon Goldwater is affiliated with the University of Edinburgh in the United Kingdom. Their research primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Signal Processing, Developmental and Educational Psychology, Experimental and Cognitive Psychology, and Human-Computer Interaction.

The scientist's work covers a range of topics, among which are:

  • Speech Recognition and Synthesis
  • Natural Language Processing Techniques
  • Topic Modeling
  • Language Development and Disorders
  • Music and Audio Processing
  • Speech and Audio Processing
  • Phonetics and Phonology Research

Sharon Goldwater has contributed to various publication venues. Most frequently, their work appears in arXiv (Cornell University). They also have publications in:

  • Language Resources and Evaluation
  • Proceedings of the National Academy of Sciences
  • Open Mind
  • ACM Transactions on Social Computing

The scientist maintains active collaborative relationships with frequent co-authors, including Walid Magdy, Yevgen Matusevych, Herman Kamper, Naomi H. Feldman, and Alexander Robertson.

Significant recent papers by Sharon Goldwater include:

  • Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input (2021, Proceedings of the National Academy of Sciences)
  • Do Infants Really Learn Phonetic Categories? (2021, Open Mind)
  • Emoji Skin Tone Modifiers (2020, ACM Transactions on Social Computing)
  • Black or White but Never Neutral: How Readers Perceive Identity from Yellow or Skin-toned Emoji (2021, Proceedings of the ACM on Human-Computer Interaction)
  • Infant Phonetic Learning as Perceptual Space Learning: A Crosslinguistic Evaluation of Computational Models (2023, Cognitive Science)

Best Publications

  • Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

    Sharon Goldwater;Tom Griffiths

  • Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

    Christos Christodoulopoulos;Sharon Goldwater;Mark Steedman

  • A Bayesian framework for word segmentation: Exploring the effects of context

    Sharon Goldwater;Thomas L. Griffiths;Mark Johnson

  • Proceedings of the Conference on Empirical Methods in Natural Language Processing

    Christos Christodoulopoulos;Sharon Goldwater;Mark Steedman

  • Learning OT constraint rankings using a maximum entropy model

    Sharon Goldwater;Mark Johnson

  • A fully Bayesian approach to unsupervised part-of-speech tagging

    Sharon Goldwater;Tom Griffiths

  • Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification

    Tom Kwiatkowksi;Luke Zettlemoyer;Sharon Goldwater;Mark Steedman

  • Bayesian Inference for PCFGs via Markov Chain Monte Carlo

    Mark Johnson;Thomas Griffiths;Sharon Goldwater

  • Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models

    Mark Johnson;Thomas L. Griffiths;Sharon Goldwater

  • Contextual Dependencies in Unsupervised Word Segmentation

    Sharon Goldwater;Thomas L. Griffiths;Mark Johnson

  • Interpolating between types and tokens by estimating power-law generators

    Sharon Goldwater;Mark Johnson;Thomas L. Griffiths

  • Lexical Generalization in CCG Grammar Induction for Semantic Parsing

    Tom Kwiatkowski;Luke Zettlemoyer;Sharon Goldwater;Mark Steedman

  • Improving Statistical MT through Morphological Analysis

    Sharon Goldwater;David McClosky

  • A Role for the Developing Lexicon in Phonetic Category Acquisition

    Naomi H. Feldman;Thomas L. Griffiths;Sharon Goldwater;James L. Morgan

  • Modeling human performance in statistical word segmentation

    Michael C. Frank;Sharon Goldwater;Thomas L. Griffiths;Joshua B. Tenenbaum

  • Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates

    Sharon Goldwater;Daniel Jurafsky;Christopher D. Manning

  • Two Decades of Unsupervised POS Induction: How Far Have We Come?

    Christos Christodoulopoulos;Sharon Goldwater;Mark Steedman

  • Pre-training on high-resource speech recognition improves low-resource speech-to-text translation

    Sameer Bansal;Herman Kamper;Karen Livescu;Adam Lopez

  • Improving nonparameteric Bayesian inference: experiments on unsupervised word segmentation with adaptor grammars

    Mark Johnson;Sharon Goldwater

  • Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

    Bevan Jones;Mark Johnson;Sharon Goldwater

  • Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics

    Trevor Cohn;Sharon Goldwater;Phil Blunsom

Frequent Co-Authors

Mark Johnson
Mark Johnson Macquarie University
Mark Steedman
Mark Steedman University of Edinburgh
Thomas L. Griffiths
Thomas L. Griffiths Princeton University
Aren Jansen
Aren Jansen Google (United States)
Phil Blunsom
Phil Blunsom University of Oxford
Karen Livescu
Karen Livescu Toyota Technological Institute at Chicago
Trevor Cohn
Trevor Cohn University of Melbourne
Walid Magdy
Walid Magdy University of Edinburgh
Frank Keller
Frank Keller University of Edinburgh
Michael C. Frank
Michael C. Frank Stanford University

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