World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
10001
World Ranking
7119
National Ranking
62

Hung-yi Lee 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 Hung-yi Lee 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: 594 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Hung-yi Lee 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 Hung-yi Lee 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Hung-yi Lee is affiliated with National Taiwan University in Taiwan and has contributed extensively to research in computer science, particularly in the domains of artificial intelligence and signal processing.

The scientist's publications focus on several key areas within computer science, including:

  • Artificial Intelligence
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • General Health Professions
  • Experimental and Cognitive Psychology

The main topics of their research include:

  • Speech Recognition and Synthesis
  • Natural Language Processing Techniques
  • Topic Modeling
  • Music and Audio Processing
  • Speech and Audio Processing
  • Speech and Dialogue Systems
  • Adversarial Robustness in Machine Learning

Frequent publication venues for Hung-yi Lee's work are:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • Interspeech 2022
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2022 IEEE Spoken Language Technology Workshop (SLT)

Selected recent papers authored or co-authored include:

  • "TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech" (2021) in IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Self-Supervised Speech Representation Learning: A Review" (2022) in IEEE Journal of Selected Topics in Signal Processing
  • "MFA-Conformer: Multi-scale Feature Aggregation Conformer for Automatic Speaker Verification" (2022) in Interspeech 2022
  • "Distilhubert: Speech Representation Learning by Layer-Wise Distillation of Hidden-Unit Bert" (2022) in ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "SUPERB: Speech processing Universal PERformance Benchmark" (2021) in arXiv (Cornell University)

Collaborative efforts frequently involve co-authors such as:

  • Haibin Wu
  • Shang-Wen Li
  • Shinji Watanabe
  • Guan-Ting Lin
  • Helen Meng

Best Publications

  • Temporal pattern attention for multivariate time series forecasting

    Shun-Yao Shih;Fan-Keng Sun;Hung-yi Lee

  • SUPERB: Speech processing Universal PERformance Benchmark

    Shu-wen Yang;Po-Han Chi;Yung-Sung Chuang;Cheng-I Jeff Lai

  • Self-Supervised Speech Representation Learning: A Review

    Unknown

  • Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders

    Andy T. Liu;Shu-wen Yang;Po-Han Chi;Po-chun Hsu

  • TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech

    Andy T. Liu;Shang-Wen Li;Hung-yi Lee

  • TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech

    Andy T. Liu;Shang-Wen Li;Hung-yi Lee

  • One-Shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization.

    Ju-chieh Chou;Cheng-chieh Yeh;Hung-yi Lee

  • Can Large Language Models Be an Alternative to Human Evaluations?

    Unknown

  • Audio Word2Vec: Unsupervised Learning of Audio Segment Representations Using Sequence-to-Sequence Autoencoder.

    Yu-An Chung;Chao-Chung Wu;Chia-Hao Shen;Hung-Yi Lee

  • Audio Albert: A Lite Bert for Self-Supervised Learning of Audio Representation

    Po-Han Chi;Pei-Hung Chung;Tsung-Han Wu;Chun-Cheng Hsieh

  • Multi-target Voice Conversion without Parallel Data by Adversarially Learning Disentangled Audio Representations

    Ju-Chieh Chou;Cheng-chieh Yeh;Hung-yi Lee;Lin-Shan Lee

  • LAMOL: LAnguage MOdeling for Lifelong Language Learning

    Fan-Keng Sun;Cheng-Hao Ho;Hung-Yi Lee

  • Tree transformer: Integrating tree structures into self-attention

    Yaushian Wang;Hung-Yi Lee;Yun-Nung Chen

  • Can Large Language Models Be an Alternative to Human Evaluations?

    Unknown

  • MFA-Conformer: Multi-scale Feature Aggregation Conformer for Automatic Speaker Verification

    Unknown

  • Spoken content retrieval: beyond cascading speech recognition with text retrieval

    Lin-shan Lee;James Glass;Hung-yi Lee;Chun-an Chan

  • SpeechBERT: An audio-and-text jointly learned language model for end-to-end spoken question answering

    Yung-Sung Chuang;Chi-Liang Liu;Hung-yi Lee;Lin-shan Lee

  • DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs

    Yi-Lin Tuan;Yun-Nung Chen;Hung-yi Lee

  • Supervised and Unsupervised Transfer Learning for Question Answering

    Yu-An Chung;Hung-yi Lee;James R. Glass

  • Again-VC: A One-Shot Voice Conversion Using Activation Guidance and Adaptive Instance Normalization

    Yen-Hao Chen;Da-Yi Wu;Tsung-Han Wu;Hung-yi Lee

  • DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERT

    Heng-Jui Chang;Shu-wen Yang;Hung-yi Lee

  • Meta Learning for End-To-End Low-Resource Speech Recognition

    Jui-Yang Hsu;Yuan-Jui Chen;Hung-yi Lee

  • Learning Chinese Word Representations From Glyphs Of Characters.

    Tzu-ray Su;Hung-yi Lee

  • Neural Attention Models for Sequence Classification: Analysis and Application to Key Term Extraction and Dialogue Act Detection.

    Sheng-syun Shen;Hung-Yi Lee

  • Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension.

    Chia-Hsuan Li;Szu-Lin Wu;Chi-Liang Liu;Hung-yi Lee

  • VQVC+: One-shot voice conversion by vector quantization and U-Net architecture

    Da-Yi Wu;Yen-Hao Chen;Hung-yi Lee

  • One-Shot Voice Conversion by Vector Quantization

    Da-Yi Wu;Hung-yi Lee

Frequent Co-Authors

Lin-Shan Lee
Lin-Shan Lee National Taiwan University
Yun-Nung Chen
Yun-Nung Chen National Taiwan University
Yu Tsao
Yu Tsao Research Center for Information Technology Innovation, Academia Sinica
Helen Meng
Helen Meng Chinese University of Hong Kong
Abdel-rahman Mohamed
Abdel-rahman Mohamed Facebook (United States)
Hsin-Min Wang
Hsin-Min Wang Academia Sinica
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
David Chiang
David Chiang University of Notre Dame

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