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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
44
Citations
10942
World Ranking
7440
National Ranking
103

Research.com Recognitions

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

Overview

Takao Kobayashi is affiliated with the Tokyo Institute of Technology in Japan. Their research spans multiple fields, primarily focusing on medicine and computer science.

The main areas of study include:

  • Medicine
  • Computer Science

Within these fields, Kobayashi has contributed to various subfields, such as:

  • Artificial Intelligence
  • Materials Chemistry
  • Public Health, Environmental and Occupational Health
  • Electrical and Electronic Engineering
  • Reproductive Medicine

Their research addresses a range of topics including:

  • Quantum Computing Algorithms and Architecture
  • Quantum Information and Cryptography
  • Endometriosis Research and Treatment
  • Uterine Myomas and Treatments
  • Machine Learning in Materials Science
  • Molecular Junctions and Nanostructures
  • Photochromic and Fluorescence Chemistry

Kobayashi has published extensively in several venues, frequently contributing to:

  • Fertility and Sterility
  • Intelligent Computing
  • arXiv (Cornell University)
  • Physical Review Research
  • Journal of Chemical Theory and Computation

Recent papers authored or co-authored by Kobayashi include:

  • "Calculating transition amplitudes by variational quantum deflation," 2022, Physical Review Research
  • "Analytical Energy Gradient for State-Averaged Orbital-Optimized Variational Quantum Eigensolvers and Its Application to a Photochemical Reaction," 2022, Journal of Chemical Theory and Computation
  • "Quantum-Classical Computational Molecular Design of Deuterated High-Efficiency OLED Emitters," 2023, Intelligent Computing
  • "Efficacy and safety of the combination of estetrol 15 mg/drospirenone 3 mg in a cyclic regimen for the treatment of endometriosis-associated pain and objective gynecological findings: a multicenter, placebo-controlled, double-blind, randomized study," 2024, Fertility and Sterility
  • "Applications of quantum computing for investigations of electronic transitions in phenylsulfonyl-carbazole TADF emitters," 2021, npj Computational Materials

Kobayashi frequently collaborates with a number of researchers, including:

  • Qi Gao
  • Michihiko Sugawara
  • Naoki Yamamoto
  • Masayoshi Nogami
  • Masashi Hirayama

Best Publications

  • Speech parameter generation algorithms for HMM-based speech synthesis

    K. Tokuda;T. Yoshimura;T. Masuko;T. Kobayashi

  • Simultaneous Modeling of Spectrum, Pitch and Duration in HMM-Based Speech Synthesis

    Takayoshi Yoshimura;Keiichi Tokuda;Takashi Masuko;Takao Kobayashi

  • An adaptive algorithm for mel-cepstral analysis of speech

    T. Fukada;K. Tokuda;T. Kobayashi;S. Imai

  • Analysis of Speaker Adaptation Algorithms for HMM-Based Speech Synthesis and a Constrained SMAPLR Adaptation Algorithm

    J. Yamagishi;T. Kobayashi;Y. Nakano;K. Ogata

  • Hidden Markov models based on multi-space probability distribution for pitch pattern modeling

    K. Tokuda;T. Masuko;N. Miyazaki;T. Kobayashi

  • Speech parameter generation from HMM using dynamic features

    K. Tokuda;T. Kobayashi;S. Imai

  • Mel-generalized cepstral analysis - a unified approach to speech spectral estimation.

    Keiichi Tokuda;Takao Kobayashi;Takashi Masuko;Satoshi Imai

  • Multi-Space Probability Distribution HMM

    Keiichi Tokuda;Takashi Masuko;Noboru Miyazaki;Takao Kobayashi

  • Speech synthesis using HMMs with dynamic features

    T. Masuko;K. Tokuda;T. Kobayashi;S. Imai

  • Average-Voice-Based Speech Synthesis Using HSMM-Based Speaker Adaptation and Adaptive Training

    Junichi Yamagishi;Takao Kobayashi

  • Duration modeling for HMM-based speech synthesis.

    Takayoshi Yoshimura;Keiichi Tokuda;Takashi Masuko;Takao Kobayashi

  • Speaker Interpolation in HMM-Based Speech Synthesis System

    Takayoshi Yoshimura;Takashi Masuko;Keiichi Tokuda;Takao Kobayashi

  • Adaptation of pitch and spectrum for HMM-based speech synthesis using MLLR

    M. Tamura;T. Masuko;K. Tokuda;T. Kobayashi

  • Mixed Excitation for HMM-based Speech Synthesis

    Takayoshi Yoshimura;Keiichi Tokuda;Takashi Masuko;Takao Kobayashi

  • Hidden semi-Markov model based speech synthesis.

    Heiga Zen;Keiichi Tokuda;Takashi Masuko;Takao Kobayashi

  • Acoustic Modeling of Speaking Styles and Emotional Expressions in HMM-Based Speech Synthesis

    Junichi Yamagishi;Koji Onishi;Takashi Masuko;Takao Kobayashi

  • An algorithm for speech parameter generation from continuous mixture HMMs with dynamic features

    Keiichi Tokuda;Takashi Masuko;Tetsuya Yamada;Takao Kobayashi

  • A Style Control Technique for HMM-Based Expressive Speech Synthesis

    Takashi Nose;Junichi Yamagishi;Takashi Masuko;Takashi Masuko;Takao Kobayashi

  • Speaker adaptation for HMM-based speech synthesis system using MLLR.

    Masatsune Tamura;Takashi Masuko;Keiichi Tokuda;Takao Kobayashi

  • Speech Synthesis with Various Emotional Expressions and Speaking Styles by Style Interpolation and Morphing

    Makoto Tachibana;Junichi Yamagishi;Takashi Masuko;Takao Kobayashi

Frequent Co-Authors

Keiichi Tokuda
Keiichi Tokuda Nagoya Institute of Technology
Takashi Masuko
Takashi Masuko Preferred Networks, Inc.
Junichi Yamagishi
Junichi Yamagishi National Institute of Informatics
Satoshi Nakamura
Satoshi Nakamura Nara Institute of Science and Technology
Shigeki Sagayama
Shigeki Sagayama University of Tokyo
Heiga Zen
Heiga Zen Google (United States)
Tomoki Toda
Tomoki Toda Nagoya University
Tatsuya Kawahara
Tatsuya Kawahara Kyoto University

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