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Hiroshi Sawada

Hiroshi Sawada

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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
51
Citations
9795
World Ranking
5369
National Ranking
67

Research.com Recognitions

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

Overview

Hiroshi Sawada is affiliated with NTT in Japan and has made contributions primarily in the fields of Computer Science and Engineering. Their research spans various subfields including Signal Processing, Electrical and Electronic Engineering, Computational Mechanics, Materials Chemistry, and Artificial Intelligence.

The scientist's expertise encompasses multiple topics such as Speech and Audio Processing, Blind Source Separation Techniques, Advanced Adaptive Filtering Techniques, Optical Network Technologies, Electronic and Structural Properties of Oxides, Neural Networks, and Reservoir Computing, and Photonic and Optical Devices.

Frequent collaborators of Hiroshi Sawada include Rintaro Ikeshita, Tomohiro Nakatani, Takuma Otsuka, Keisuke Kinoshita, and Kazuo Aoyama.

Regarding publication venues, the most frequent sites for their work include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • NTT technical review
  • npj Computational Materials
  • Proceedings of the AAAI Conference on Artificial Intelligence

Some of the recent papers authored or co-authored by Hiroshi Sawada are:

  • Bayesian optimization with experimental failure for high-throughput materials growth, 2022, npj Computational Materials
  • A Joint Diagonalization Based Efficient Approach to Underdetermined Blind Audio Source Separation Using the Multichannel Wiener Filter, 2021, 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
  • Bayesian Unification of Sound Source Localization and Separation with Permutation Resolution, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Intrinsic physics in magnetic Weyl semimetal SrRuO3 films addressed by machine-learning-assisted molecular beam epitaxy, 2022, Japanese Journal of Applied Physics

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

  • Blind speech separation

    Shoji Makino;Hiroshi Sawada;Te-Won Lee

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

    Hiroshi Sawada;Shoko Araki;Shoji Makino

  • Determined blind source separation unifying independent vector analysis and nonnegative matrix factorization

    Daichi Kitamura;Nobutaka Ono;Hiroshi Sawada;Hirokazu Kameoka

  • Minimization of binary decision diagrams based on exchanges of variables

    N. Ishiura;H. Sawada;S. Yajima

  • 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

  • First stereo audio source separation evaluation campaign: data, algorithms and results

    Emmanuel Vincent;Hiroshi Sawada;Pau Bofill;Shoji Makino

  • 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

  • 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

  • Map-based underdetermined blind source separation of convolutive mixtures by hierarchical clustering and l 1 -norm minimization

    Stefan Winter;Walter Kellermann;Hiroshi Sawada;Shoji 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

  • Natural gradient multichannel blind deconvolution and speech separation using causal FIR filters

    S.C. Douglas;H. Sawada;S. Makino

  • A review of blind source separation methods: two converging routes to ILRMA originating from ICA and NMF

    Hiroshi Sawada;Nobutaka Ono;Hirokazu Kameoka;Daichi Kitamura

  • Automatic inference of cross-modal nonverbal interactions in multiparty conversations: "who responds to whom, when, and how?" from gaze, head gestures, and utterances

    Kazuhiro Otsuka;Hiroshi Sawada;Junji Yamato

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

    Mehrez Souden;Shoko Araki;Keisuke Kinoshita;Tomohiro Nakatani

  • Spatio–Temporal FastICA Algorithms for the Blind Separation of Convolutive Mixtures

    S.C. Douglas;M. Gupta;H. Sawada;S. Makino

  • Fashion coordinates recommender system using photographs from fashion magazines

    Tomoharu Iwata;Shinji Watanabe;Hiroshi Sawada

Frequent Co-Authors

Shoji Makino
Shoji Makino Waseda University
Shoko Araki
Shoko Araki NTT (Japan)
Hirokazu Kameoka
Hirokazu Kameoka NTT (Japan)
Hiroshi Saruwatari
Hiroshi Saruwatari University of Tokyo
Scott C. Douglas
Scott C. Douglas Southern Methodist University
Makoto Yokoo
Makoto Yokoo Kyushu University
Nobutaka Ono
Nobutaka Ono Tokyo Metropolitan University

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