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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
55
Citations
12569
World Ranking
4299
National Ranking
42

Masataka Goto 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 Masataka Goto 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 355 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Masataka Goto 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 Masataka Goto sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Masataka Goto is affiliated with the National Institute of Advanced Industrial Science and Technology in Japan. Their research spans the fields of Computer Science, with a particular focus on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, and Music.

Their main topics of work include Music and Audio Processing, Music Technology and Sound Studies, Speech and Audio Processing, Video Analysis and Summarization, Speech Recognition and Synthesis, Neuroscience and Music Perception, and Natural Language Processing Techniques.

They have contributed to numerous publications across various venues. Frequent publication venues include IEICE Transactions on Information and Systems, arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), IEEE/ACM Transactions on Audio Speech and Language Processing, and Transactions of the International Society for Music Information Retrieval.

Among their recent papers are:

  • Sequential gallery for interactive visual design optimization, 2020, ACM Transactions on Graphics
  • Intelligent User Interfaces for Music Discovery, 2020, Transactions of the International Society for Music Information Retrieval
  • Audio-to-score singing transcription based on a CRNN-HSMM hybrid model, 2021, APSIPA Transactions on Signal and Information Processing
  • Self-Supervised Contrastive Learning for Singing Voices, 2022, IEEE/ACM Transactions on Audio Speech and Language Processing
  • Deep Learning Approaches in Topics of Singing Information Processing, 2022, IEEE/ACM Transactions on Audio Speech and Language Processing

Masataka Goto has collaborated extensively with other researchers, including Masahiro Hamasaki, Kosetsu Tsukuda, Yuki Koyama, Tomoyasu Nakano, and Satoru Fukayama.

In addition to journal articles, they have contributed to book publications, including a title published by the European Organization for Nuclear Research: Proceedings of the 23nd International Society for Music Information Retrieval Conference, 2022.

Best Publications

  • Content-Based Music Information Retrieval: Current Directions and Future Challenges

    M.A. Casey;R. Veltkamp;M. Goto;M. Leman

  • RWC Music Database: Popular, Classical, and Jazz Music Databases

    Masataka Goto;Hiroki Hashiguchi;Takuichi Nishimura;Ryuichi Oka

  • RWC Music Database: Music Genre Database and Musical Instrument Sound Database

    Masataka Goto;Hiroki Hashiguchi;Takuichi Nishimura;Ryuichi Oka

  • An Audio-based Real-time Beat Tracking System for Music With or Without Drum-sounds

    Masataka Goto

  • A real-time music-scene-description system: predominant-F0 estimation for detecting melody and bass lines in real-world audio signals

    Masataka Goto

  • Speech recognition system and speech recognition system program

    Jun Ogata;Masataka Goto

  • Development of the RWC Music Database

    Masataka Goto

  • A chorus section detection method for musical audio signals and its application to a music listening station

    M. Goto

  • A chorus-section detecting method for musical audio signals

    M. Goto

  • An Efficient Hybrid Music Recommender System Using an Incrementally Trainable Probabilistic Generative Model

    K. Yoshii;M. Goto;K. Komatani;T. Ogata

  • Hybrid collaborative and content-based music recommendation using probabilistic model with latent user preferences

    Kazuyoshi Yoshii;Masataka Goto;Kazunori Komatani;Tetsuya Ogata

  • A beat tracking system for acoustic signals of music

    M. Goto;Y. Muraoka

  • AIST Annotation for the RWC Music Database.

    Masataka Goto

  • Real-time beat tracking for drumless audio signals: chord change detection for musical decisions

    Masataka Goto;Yoichi Muraoka

  • A real-time filled pause detection system for spontaneous speech recognition.

    Masataka Goto;Katunobu Itou;Satoru Hayamizu

  • A predominant-F/sub 0/ estimation method for CD recordings: MAP estimation using EM algorithm for adaptive tone models

    M. Goto

  • A robust predominant-F0 estimation method for real-time detection of melody and bass lines in CD recordings

    M. Goto

  • An Automatic Singing Skill Evaluation Method for Unknown Melodies Using Pitch Interval Accuracy and Vibrato Features

    Tomoyasu Nakano;Masataka Goto;Yuzuru Hiraga

  • Real-time sound source localization and separation system and its application to automatic speech recognition

    Futoshi Asano;Masataka Goto;Katunobu Itou;Hideki Asoh

  • Speech-to-Singing Synthesis: Converting Speaking Voices to Singing Voices by Controlling Acoustic Features Unique to Singing Voices

    Takeshi Saitou;Masataka Goto;Masashi Unoki;Masato Akagi

  • Beat tracking based on multiple-agent architecture-A real-time beat tracking system for audio signals

    M. Goto

  • Content-Based Music Information Retrieval: Current Directions and Future Challenges Current retrieval systems can handle tens-of-thousands of music tracks but new systems need to aim at huge online music collections that contain tens-of-millions of tracks.

    Michael A. Casey;Remco Veltkamp;Masataka Goto;Marc Leman

Frequent Co-Authors

Hiroshi G. Okuno
Hiroshi G. Okuno Waseda University
Tetsuya Ogata
Tetsuya Ogata Waseda University
Satoshi Nakamura
Satoshi Nakamura Nara Institute of Science and Technology
Tomoki Toda
Tomoki Toda Nagoya University
Takeo Igarashi
Takeo Igarashi University of Tokyo
Graham Neubig
Graham Neubig Carnegie Mellon University
Sakriani Sakti
Sakriani Sakti Nara Institute of Science and Technology
Kazuya Takeda
Kazuya Takeda Nagoya University
Malcolm Slaney
Malcolm Slaney Stanford University
Ryota Tomioka
Ryota Tomioka Microsoft (United States)

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