D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 38 Citations 7,155 334 World Ranking 4959 National Ranking 77

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Speech recognition

Kazuya Takeda mainly focuses on Speech recognition, Artificial intelligence, Natural language processing, Mixture model and Simulation. His Speech recognition research includes elements of Speech enhancement, Noise reduction and Reverberation. His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Relevance, Vocabulary and Computer vision.

Kazuya Takeda has researched Natural language processing in several fields, including Audio-visual speech recognition, Speech corpus, Speech synthesis, Bottleneck and Thesaurus. Kazuya Takeda interconnects Soft computing, Fuzzy logic, System identification, Adaptive neuro fuzzy inference system and Multilayer perceptron in the investigation of issues within Mixture model. His Simulation study integrates concerns from other disciplines, such as Brake and Biometrics.

His most cited work include:

  • Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification (217 citations)
  • An Open Approach to Autonomous Vehicles (203 citations)
  • JNAS: Japanese speech corpus for large vocabulary continuous speech recognition research (192 citations)

What are the main themes of his work throughout his whole career to date?

Kazuya Takeda focuses on Speech recognition, Artificial intelligence, Natural language processing, Speech processing and Pattern recognition. His Speech recognition research is mostly focused on the topic Speech corpus. His studies deal with areas such as Machine learning and Computer vision as well as Artificial intelligence.

His study in Voice activity detection and Acoustic model is done as part of Speech processing. His studies in Acoustics integrate themes in fields like Microphone array and Frequency domain. His research integrates issues of Word recognition and Word error rate in his study of Microphone.

He most often published in these fields:

  • Speech recognition (54.10%)
  • Artificial intelligence (34.48%)
  • Natural language processing (11.24%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (34.48%)
  • Speech recognition (54.10%)
  • Computer vision (7.05%)

In recent papers he was focusing on the following fields of study:

His main research concerns Artificial intelligence, Speech recognition, Computer vision, Machine learning and Deep learning. His Artificial intelligence research incorporates elements of Trajectory and Pattern recognition. His Speech recognition research is multidisciplinary, incorporating elements of Acoustics and End-to-end principle.

The study incorporates disciplines such as Point, Volume and Visibility in addition to Computer vision. His Machine learning study combines topics from a wide range of disciplines, such as Classifier, Context, Task and Control. In his work, Mean opinion score and Transformer is strongly intertwined with Natural language processing, which is a subfield of Speech processing.

Between 2015 and 2021, his most popular works were:

  • Speaker-Dependent WaveNet Vocoder. (181 citations)
  • A Survey of Autonomous Driving: Common Practices and Emerging Technologies (150 citations)
  • An investigation of multi-speaker training for wavenet vocoder (76 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Machine learning

Kazuya Takeda mostly deals with Artificial intelligence, Speech recognition, Deep learning, Pattern recognition and Hidden Markov model. Kazuya Takeda focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Computer vision and, in some cases, Image compression and Volume. His research in the fields of Voice activity detection overlaps with other disciplines such as Thresholding.

The various areas that he examines in his Deep learning study include Feature, Traffic conditions and CLIPS. His study in the field of Feature extraction is also linked to topics like Modal. In his study, Semantics and Cluster analysis is inextricably linked to Chunking, which falls within the broad field of Hidden Markov model.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

ATR Japanese speech database as a tool of speech recognition and synthesis

Akira Kurematsu;Kazuya Takeda;Yoshinori Sagisaka;Shigeru Katagiri.
Speech Communication (1990)

340 Citations

JNAS: Japanese speech corpus for large vocabulary continuous speech recognition research

Katunobu Itou;Mikio Yamamoto;Kazuya Takeda;Toshiyuki Takezawa.
The Journal of The Acoustical Society of Japan (e) (1999)

331 Citations

An Open Approach to Autonomous Vehicles

Shinpei Kato;Eijiro Takeuchi;Yoshio Ishiguro;Yoshiki Ninomiya.
IEEE Micro (2015)

329 Citations

Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification

C. Miyajima;Y. Nishiwaki;K. Ozawa;T. Wakita.
Proceedings of the IEEE (2007)

317 Citations

Evaluation of blind signal separation method using directivity pattern under reverberant conditions

S. Kurita;H. Saruwatari;S. Kajita;K. Takeda.
international conference on acoustics, speech, and signal processing (2000)

279 Citations

Blind source separation combining independent component analysis and beamforming

Hiroshi Saruwatari;Satoshi Kurita;Kazuya Takeda;Fumitada Itakura.
EURASIP Journal on Advances in Signal Processing (2003)

246 Citations

Speaker-Dependent WaveNet Vocoder.

Akira Tamamori;Tomoki Hayashi;Kazuhiro Kobayashi;Kazuya Takeda.
conference of the international speech communication association (2017)

223 Citations

Analysis and recognition of whispered speech

Taisuke Ito;Kazuya Takeda;Fumitada Itakura.
Speech Communication (2005)

222 Citations

A Survey of Autonomous Driving: Common Practices and Emerging Technologies

Ekim Yurtsever;Jacob Lambert;Alexander Carballo;Kazuya Takeda.
IEEE Access (2020)

183 Citations

Free software toolkit for Japanese large vocabulary continuous speech recognition

Tatsuya Kawahara;Akinobu Lee;Tetsunori Kobayashi;Kazuya Takeda.
international conference on spoken language processing (2000)

154 Citations

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