World's Best Scientists 2026 revealed!
Shoko Araki

Shoko Araki

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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
51
Citations
9657
World Ranking
5378
National Ranking
68

Shoko Araki 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 Shoko Araki 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: 267 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Shoko Araki 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 Shoko Araki 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: 51 D-Index — 63rd percentile

63% 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

Shoko Araki is affiliated with NTT in Japan and has published extensively within the field of Computer Science, focusing predominantly on Signal Processing and its various subfields. Their research spans topics such as Speech and Audio Processing, Speech Recognition and Synthesis, Music and Audio Processing, Advanced Adaptive Filtering Techniques, Blind Source Separation Techniques, Hearing Loss and Rehabilitation, and Underwater Acoustics Research.

Their recent publications include:

  • "How bad are artifacts?: Analyzing the impact of speech enhancement errors on ASR" (2022, Interspeech 2022)
  • "Block Coordinate Descent Algorithms for Auxiliary-Function-Based Independent Vector Extraction" (2021, IEEE Transactions on Signal Processing)
  • "SoundBeam: Target Sound Extraction Conditioned on Sound-Class Labels and Enrollment Clues for Increased Performance and Continuous Learning" (2022, IEEE/ACM Transactions on Audio Speech and Language Processing)
  • "Mask-Based Neural Beamforming for Moving Speakers With Self-Attention-Based Tracking" (2023, IEEE/ACM Transactions on Audio Speech and Language Processing)
  • "Switching Independent Vector Analysis and its Extension to Blind and Spatially Guided Convolutional Beamforming Algorithms" (2022, IEEE/ACM Transactions on Audio Speech and Language Processing)

Frequent co-authors who have collaborated often with Shoko Araki include:

  • Marc Delcroix
  • Tomohiro Nakatani
  • Tsubasa Ochiai
  • Keisuke Kinoshita
  • Rintaro Ikeshita

Their publications are regularly featured in a variety of venues, notably:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
  • NTT technical review
  • 2021 29th European Signal Processing Conference (EUSIPCO)

Shoko Araki's work reflects a focus on innovative approaches to audio and speech signal processing, including research on neural beamforming, independent vector analysis, and algorithms that enhance speech recognition accuracy and sound extraction. Their scientific contributions encompass both theoretical and applied aspects, contributing to evolving technologies in speech enhancement and auditory scene analysis.

Best Publications

  • A robust and precise method for solving the permutation problem of frequency-domain blind source separation

    H. Sawada;R. Mukai;S. Araki;S. Makino

  • The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech

    S. Araki;R. Mukai;S. Makino;T. Nishikawa

  • Underdetermined Convolutive Blind Source Separation via Frequency Bin-Wise Clustering and Permutation Alignment

    Hiroshi Sawada;Shoko Araki;Shoji Makino

  • Multichannel Extensions of Non-Negative Matrix Factorization With Complex-Valued Data

    H. Sawada;H. Kameoka;S. Araki;N. Ueda

  • Underdetermined blind sparse source separation for arbitrarily arranged multiple sensors

    Shoko Araki;Hiroshi Sawada;Ryo Mukai;Shoji Makino

  • The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices

    Takuya Yoshioka;Nobutaka Ito;Marc Delcroix;Atsunori Ogawa

  • Polar coordinate based nonlinear function for frequency-domain blind source separation

    Hiroshi Sawada;Ryo Mukai;Shoko Araki;Shoji Makino

  • The signal separation evaluation campaign (2007-2010): Achievements and remaining challenges

    Emmanuel Vincent;Shoko Araki;Fabian Theis;Guido Nolte

  • The 2011 signal separation evaluation campaign (SiSEC2011): - audio source separation -

    Shoko Araki;Francesco Nesta;Emmanuel Vincent;Zbyněk Koldovský

  • The 2008 Signal Separation Evaluation Campaign: A Community-Based Approach to Large-Scale Evaluation

    Emmanuel Vincent;Shoko Araki;Pau Bofill

  • Grouping Separated Frequency Components by Estimating Propagation Model Parameters in Frequency-Domain Blind Source Separation

    H. Sawada;S. Araki;R. Mukai;S. Makino

  • The 2010 signal separation evaluation campaign (SiSEC2010): audio source separation

    Shoko Araki;Alexey Ozerov;Vikrham Gowreesunker;Hiroshi Sawada

  • Measuring Dependence of Bin-wise Separated Signals for Permutation Alignment in Frequency-domain BSS

    H. Sawada;S. Araki;S. Makino

  • Blind Extraction of Dominant Target Sources Using ICA and Time-Frequency Masking

    H. Sawada;S. Araki;R. Mukai;S. Makino

  • Frequency-Domain Blind Source Separation

    Shoji Makino;Hiroshi Sawada;Shoko Araki

  • A Multichannel MMSE-Based Framework for Speech Source Separation and Noise Reduction

    Mehrez Souden;Shoko Araki;Keisuke Kinoshita;Tomohiro Nakatani

  • Improving Speaker Discrimination of Target Speech Extraction With Time-Domain Speakerbeam

    Marc Delcroix;Tsubasa Ochiai;Katerina Zmolikova;Keisuke Kinoshita

  • Exploring multi-channel features for denoising-autoencoder-based speech enhancement

    Shoko Araki;Tomoki Hayashi;Marc Delcroix;Masakiyo Fujimoto

  • Online MVDR Beamformer Based on Complex Gaussian Mixture Model With Spatial Prior for Noise Robust ASR

    Takuya Higuchi;Nobutaka Ito;Shoko Araki;Takuya Yoshioka

  • A Two-Stage Frequency-Domain Blind Source Separation Method for Underdetermined Convolutive Mixtures

    Hiroshi Sawada;Shoko Araki;Shoji Makino

  • Low-Latency Real-Time Meeting Recognition and Understanding Using Distant Microphones and Omni-Directional Camera

    T. Hori;S. Araki;T. Yoshioka;M. Fujimoto

Frequent Co-Authors

Shoji Makino
Shoji Makino Waseda University
Hiroshi Sawada
Hiroshi Sawada NTT (Japan)
Marc Delcroix
Marc Delcroix NTT (Japan)
Takuya Yoshioka
Takuya Yoshioka Microsoft (United States)
Hiroshi Saruwatari
Hiroshi Saruwatari University of Tokyo
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Hirokazu Kameoka
Hirokazu Kameoka NTT (Japan)
Nobutaka Ono
Nobutaka Ono Tokyo Metropolitan University

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