Jun Ogata

1.4k citations
65 papers · 1.1k · h-index 17

Impact in

Papers in

    • Speech Recognition and Synthesis 26
    • Speech and dialogue systems 8
    • Natural Language Processing Techniques 8
    • Music and Audio Processing 27
    • Speech and Audio Processing 24

Jun Ogata

60 papers receiving 946 citations

Peers

Jun Ogata
Comparison fields: 5 of 95
  • Signal Processing 465
  • Computer Vision and Pattern Recognition 370
  • Artificial Intelligence 465
  • Human-Computer Interaction 56
  • Computer Science Applications 27
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Raymond Ptucha United States
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Haytham M. Fayek Australia
Plínio Moreno Portugal
Aggelos Pikrakis Greece
Aparecido Nilceu Marana Brazil
Dar-Shyang Lee United States
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Citations per field
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Citations per year

Countries citing papers authored by Jun Ogata

Since Specialization
Citations

This map shows the geographic impact of Jun Ogata's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Ogata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Ogata more than expected).

Fields of papers citing papers by Jun Ogata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Ogata. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Ogata. The network helps show where Jun Ogata may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun Ogata, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Ogata Line = papers co-authored together Jun Ogata links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005159
2 200599
3 200671
4 201167
5 200655
6 200746
7 200537
8 200335
9 200633
10 200731
11
An application of a particle filter to Bayesian multiple sound source tracking with audio and video information fusion
200428
12 200728
13 200727
14 200424
15 200924
16 201117
17 200817
18 202116
19 200416
20 201915

About Jun Ogata

Jun Ogata is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 65 papers that have together received 1.1k indexed citations. Recurring topics across this work include Music and Audio Processing (27 papers), Speech Recognition and Synthesis (26 papers), Speech and Audio Processing (24 papers), Speech and dialogue systems (8 papers), Natural Language Processing Techniques (8 papers), Machine Fault Diagnosis Techniques (7 papers), Structural Health Monitoring Techniques (5 papers) and Radio, Podcasts, and Digital Media (5 papers). The work is most often cited by research in Signal Processing (465 citations), Computer Vision and Pattern Recognition (370 citations), Artificial Intelligence (465 citations), Human-Computer Interaction (56 citations) and Computer Science Applications (27 citations). Jun Ogata has collaborated with scholars based in Japan, Germany and United States. Frequent co-authors include Masataka Goto, Atsushi Yoshizawa, Makoto Yamamoto, Yasuo Ariki, Hiromasa Fujihara, Hiroshi G. Okuno, Kiyoshi Yamamoto, Hideki Asoh, Futoshi Asano and Takeo Igarashi. Their work appears in journals such as Structural Concrete, Atmospheric chemistry and physics, IEEE Journal of Selected Topics in Signal Processing, Electric Power Systems Research and Climate of the past.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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