World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
12554
World Ranking
9963
National Ranking
21

Jan Cernocky 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 Jan Cernocky 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: 181 publications — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Jan Cernocky 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 Jan Cernocky 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: 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.

Overview

Jan Cernocky is affiliated with Brno University of Technology in the Czech Republic. Their research focuses on the field of Computer Science, with a strong emphasis on Artificial Intelligence and Signal Processing. The work also extends to General Health Professions, Physiology, and Experimental and Cognitive Psychology in a limited capacity.

The main topics covered by their research include Speech Recognition and Synthesis, Speech and Audio Processing, Music and Audio Processing, Natural Language Processing Techniques, Topic Modeling, Speech and Dialogue Systems, and AI in Service Interactions.

Frequent coauthors in their publications include Lukáš Burget, Oldřich Plchot, Ladislav Mošner, Junyi Peng, and Themos Stafylakis.

Jan Cernocky has published extensively in notable venues. Among the most frequent are arXiv (Cornell University), Interspeech 2022, ICASSP 2022 (IEEE International Conference on Acoustics, Speech and Signal Processing), IEEE Signal Processing Magazine, and the 2022 IEEE Spoken Language Technology Workshop (SLT).

Notable recent papers authored or coauthored by Jan Cernocky include:

  • Neural Target Speech Extraction: An overview (2023), IEEE Signal Processing Magazine
  • Speaker adaptation for Wav2vec2 based dysarthric ASR (2022), Interspeech 2022
  • An Attention-Based Backend Allowing Efficient Fine-Tuning of Transformer Models for Speaker Verification (2023), 2022 IEEE Spoken Language Technology Workshop (SLT)
  • DPCCN: Densely-Connected Pyramid Complex Convolutional Network for Robust Speech Separation and Extraction (2022), ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communications (2022), arXiv (Cornell University)

Best Publications

  • Extensions of recurrent neural network language model

    Tomas Mikolov;Stefan Kombrink;Lukas Burget;Jan Cernocky

  • Strategies for training large scale neural network language models

    Tomas Mikolov;Anoop Deoras;Daniel Povey;Lukas Burget

  • Probabilistic and Bottle-Neck Features for LVCSR of Meetings

    F. Grezl;M. Karafiat;S. Kontar;J. Cernocky

  • RNNLM - Recurrent Neural Network Language Modeling Toolkit

    Tomas Mikolov;Stefan Kombrink;Anoop Deoras;Lukas Burget

  • Fusion of Heterogeneous Speaker Recognition Systems in the STBU Submission for the NIST Speaker Recognition Evaluation 2006

    N. Brummer;L. Burget;J.H. Cernocky;O. Glembek

  • Bi-Modal Person Recognition on a Mobile Phone: Using Mobile Phone Data

    Christopher McCool;Sebastien Marcel;Abdenour Hadid;Matti Pietikainen

  • Hierarchical Structures of Neural Networks for Phoneme Recognition

    P. Schwarz;P. Matejka;J. Cernocky

  • Comparison of keyword spotting approaches for informal continuous speech.

    Igor Szöke;Petr Schwarz;Pavel Matejka;Lukás Burget

  • Improved feature processing for Deep Neural Networks

    Shakti P. Rath;Daniel Povey;Karel Veselý;Jan Cernocký

  • Full-covariance UBM and heavy-tailed PLDA in i-vector speaker verification

    Pavel Matejka;Ondrej Glembek;Fabio Castaldo;M.J. Alam

  • SpeakerBeam: Speaker Aware Neural Network for Target Speaker Extraction in Speech Mixtures

    Katerina Zmolikova;Marc Delcroix;Keisuke Kinoshita;Tsubasa Ochiai

  • Analysis of Feature Extraction and Channel Compensation in a GMM Speaker Recognition System

    L. Burget;P. Matejka;P. Schwarz;O. Glembek

  • Towards Lower Error Rates in Phoneme Recognition

    Petr Schwarz;Pavel Matějka;Jan Černocký

  • Neural network based language models for highly inflective languages

    Tomas Mikolov;Jiri Kopecky;Lukas Burget;Ondrej Glembek

  • Brno University of Technology System for NIST 2005 Language Recognition Evaluation

    P. Matejka;L. Burget;P. Sckwarz;J. Cernocky

  • Analysis of DNN approaches to speaker identification

    Pavel Matejka;Ondrej Glembek;Ondrej Novotny;Oldrich Plchot

  • Analysis of Score Normalization in Multilingual Speaker Recognition.

    Pavel Matějka;Ondřej Novotný;Oldřich Plchot;Lukáš Burget

  • Discriminative Training Techniques for Acoustic Language Identification

    L. Burget;P. Matejka;J. Cernocky

  • Building and Evaluation of a Real Room Impulse Response Dataset

    Igor Szoke;Miroslav Skacel;Ladislav Mosner;Jakub Paliesek

  • Variational Inference for Acoustic Unit Discovery

    Lucas Ondel;Lukaš Burget;Jan Černocký

Frequent Co-Authors

Lukas Burget
Lukas Burget Brno University of Technology
Martin Karafiat
Martin Karafiat Brno University of Technology
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Tomas Mikolov
Tomas Mikolov Czech Technical University in Prague
Marc Delcroix
Marc Delcroix NTT (Japan)
Sébastien Marcel
Sébastien Marcel Idiap Research Institute
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Jean-Marc Odobez
Jean-Marc Odobez Idiap Research Institute
Hervé Bourlard
Hervé Bourlard Idiap Research Institute
Hynek Hermansky
Hynek Hermansky Johns Hopkins University

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