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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 38 10391 10099 650 642 145 4850

William Byrne publications per year

The chart shows the history of publications by William Byrne between 1985 and 2019, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. William Byrne published across 35 years, from 1985 to 2019, averaging 4.1 papers a year. Output peaked at 12 publications in 2003. 1 of the 145 publications appeared in the last two years.

No. of publications
5 10
Bar chart. Horizontal axis: year, 1985 to 2019. Vertical axis: number of publications, 0 to 12. Peak 12 publications in 2003. 1985: 1 publication 1986: 1 publication 1987: 0 publications 1988: 0 publications 1989: 1 publication 1990: 0 publications 1991: 0 publications 1992: 1 publication 1993: 3 publications 1994: 1 publication 1995: 0 publications 1996: 1 publication 1997: 1 publication 1998: 3 publications 1999: 9 publications 2000: 10 publications 2001: 10 publications 2002: 11 publications 2003: 12 publications 2004: 10 publications 2005: 11 publications 2006: 10 publications 2007: 4 publications 2008: 6 publications 2009: 10 publications 2010: 12 publications 2011: 4 publications 2012: 3 publications 2013: 6 publications 2014: 2 publications 2015: 0 publications 2016: 1 publication 2017: 0 publications 2018: 0 publications 2019: 1 publication
1985 2019

145 publications in total across all disciplines

View publications per year as a table
William Byrne: publications per year, 1985 to 2019
Year Publications
1985 1
1986 1
1987 0
1988 0
1989 1
1990 0
1991 0
1992 1
1993 3
1994 1
1995 0
1996 1
1997 1
1998 3
1999 9
2000 10
2001 10
2002 11
2003 12
2004 10
2005 11
2006 10
2007 4
2008 6
2009 10
2010 12
2011 4
2012 3
2013 6
2014 2
2015 0
2016 1
2017 0
2018 0
2019 1
Total 145
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William Byrne 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 William Byrne sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 142–151 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 145 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609 145
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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William Byrne 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 William Byrne sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 38–39 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968 38
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Speech recognition

William Byrne mostly deals with Artificial intelligence, Speech recognition, Natural language processing, Machine translation and Translation. A large part of his Artificial intelligence studies is devoted to Bayes' theorem. His study in Speech recognition is interdisciplinary in nature, drawing from both Normalization and Segmentation.

The study incorporates disciplines such as Czech and Vocabulary in addition to Natural language processing. His work carried out in the field of Translation brings together such families of science as Data mining and Pruning. His study in Transfer-based machine translation is interdisciplinary in nature, drawing from both Bitext word alignment and Word.

His most cited work include:

  • Minimum Bayes-risk decoding for statistical machine translation (327 citations)
  • Minimum bayes-risk automatic speech recognition (159 citations)
  • Convergence Theorems for Generalized Alternating Minimization Procedures (122 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Artificial intelligence, Speech recognition, Natural language processing, Hidden Markov model and Machine translation. His Artificial intelligence study combines topics from a wide range of disciplines, such as Decoding methods and Pattern recognition. His Speech recognition research is multidisciplinary, incorporating perspectives in Vocabulary and Discriminative model.

The Natural language processing study combines topics in areas such as Czech, Speech corpus and Translation. As part of one scientific family, William Byrne deals mainly with the area of Hidden Markov model, narrowing it down to issues related to the Estimation theory, and often Expectation–maximization algorithm. The study incorporates disciplines such as Sentence and Word in addition to Machine translation.

He most often published in these fields:

  • Artificial intelligence (69.80%)
  • Speech recognition (62.42%)
  • Natural language processing (43.62%)

What were the highlights of his more recent work (between 2007-2016)?

  • Artificial intelligence (69.80%)
  • Speech recognition (62.42%)
  • Natural language processing (43.62%)

In recent papers he was focusing on the following fields of study:

William Byrne focuses on Artificial intelligence, Speech recognition, Natural language processing, Machine translation and Phrase. William Byrne studies Artificial intelligence, namely Translation. His study in Speech synthesis, Hidden Markov model and Speaker recognition are all subfields of Speech recognition.

William Byrne does research in Natural language processing, focusing on Rule-based machine translation specifically. His work on Language translation as part of general Machine translation study is frequently linked to Simple, therefore connecting diverse disciplines of science. The various areas that William Byrne examines in his Phrase study include Language model, Theoretical computer science, Generative model and NIST.

Between 2007 and 2016, his most popular works were:

  • Hierarchical phrase-based translation with weighted finite-state transducers and shallow-n grammars (52 citations)
  • Rule Filtering by Pattern for Efficient Hierarchical Translation (42 citations)
  • Overview and results of Morpho challenge 2009 (41 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary areas of study are Artificial intelligence, Natural language processing, Speech recognition, Machine translation and Translation. William Byrne is involved in the study of Natural language processing that focuses on Rule-based machine translation in particular. His work is connected to Hidden Markov model, Speaker recognition and Speech synthesis, as a part of Speech recognition.

The concepts of his Machine translation study are interwoven with issues in Decoding methods, Word and Bayes' theorem. His Bayes' theorem study integrates concerns from other disciplines, such as Language model and Synchronous context-free grammar. William Byrne interconnects Machine learning, Pruning and Phrase in the investigation of issues within Translation.

Best Publications

  • Minimum Bayes-risk decoding for statistical machine translation

    Shankar Kumar;William J. Byrne

  • Minimum bayes-risk automatic speech recognition

    Vaibhava Goel;William J Byrne

  • Stochastic pronunciation modelling from hand-labelled phonetic corpora

    Michael Riley;William Byrne;Michael Finke;Sanjeev Khudanpur

  • Convergence Theorems for Generalized Alternating Minimization Procedures

    Asela Gunawardana;William Byrne

  • Automatic recognition of spontaneous speech for access to multilingual oral history archives

    W. Byrne;D. Doermann;M. Franz;S. Gustman

  • Towards language independent acoustic modeling

    W. Byrne;P. Beyerlein;J.M. Huerta;S. Khudanpur

  • Consensus Network Decoding for Statistical Machine Translation System Combination

    K. C. Sim;W. J. Byrne;M. J. F. Gales;H. Sahbi

  • HMM Word and Phrase Alignment for Statistical Machine Translation

    Yonggang Deng;W. Byrne

  • Local Phrase Reordering Models for Statistical Machine Translation

    Shankar Kumar;William Byrne

  • Alternating minimization and Boltzmann machine learning

    W. Byrne

  • HMM Word and Phrase Alignment for Statistical Machine Translation

    Yonggang Deng;William Byrne

  • A weighted finite state transducer translation template model for statistical machine translation

    Shankar Kumar;Yonggang Deng;William Byrne

  • On large vocabulary continuous speech recognition of highly inflectional language - Czech

    Pavel Ircing;Pavel Krbec;Jan Hajic;Josef Psutka

  • A weighted finite state transducer implementation of the alignment template model for statistical machine translation

    Shankar Kumar;William Byrne

  • Discriminative Speaker Adaptation with Conditional Maximum Likelihood Linear Regression

    Asela Gunawardana;William Byrne

  • A generative probabilistic OCR model for NLP applications

    Okan Kolak;William Byrne;Philip Resnik

  • Autoregressive Models for Statistical Parametric Speech Synthesis

    M. Shannon;Heiga Zen;W. Byrne

  • Speaker normalization with all-pass transforms

    John W. McDonough;William J. Byrne;Xiaoqiang Luo

  • Discriminative linear transforms for feature normalization and speaker adaptation in HMM estimation

    S. Tsakalidis;V. Doumpiotis;W. Byrne

  • Segmental minimum Bayes-risk decoding for automatic speech recognition

    V. Goel;S. Kumar;W. Byrne

  • Pronunciation modelling using a hand-labelled corpus for conversational speech recognition

    W. Byrne;M. Finke;S. Khunanpur;J. McDonough

  • Proceedings of the ACL 2010 System Demonstrations

    Mikko Kurimo;William Byrne;John Dines;Philip N. Garner

Frequent Co-Authors

Jan Hajič
Jan Hajič Charles University
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Mikko Kurimo
Mikko Kurimo Aalto University
Pascale Fung
Pascale Fung Hong Kong University of Science and Technology
Bhuvana Ramabhadran
Bhuvana Ramabhadran Google (United States)
Keiichi Tokuda
Keiichi Tokuda Nagoya Institute of Technology
Junichi Yamagishi
Junichi Yamagishi National Institute of Informatics
Douglas W. Oard
Douglas W. Oard University of Maryland, College Park
Philip Resnik
Philip Resnik University of Maryland, College Park
Michael Picheny
Michael Picheny IBM (United States)

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