Kenichi Kumatani

36 papers receiving 432 citations

Peers

Kenichi Kumatani
Comparison fields: 5 of 41
  • Signal Processing 417
  • Artificial Intelligence 228
  • Computational Mechanics 165
  • Electrical and Electronic Engineering 73
  • Computer Vision and Pattern Recognition 43
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Jeih-weih Hung Taiwan
Marco Matassoni Italy
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Citations per field
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Citations per year

Countries citing papers authored by Kenichi Kumatani

Since Specialization
Citations

This map shows the geographic impact of Kenichi Kumatani'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 Kenichi Kumatani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kenichi Kumatani more than expected).

Fields of papers citing papers by Kenichi Kumatani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kenichi Kumatani. 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 Kenichi Kumatani. The network helps show where Kenichi Kumatani may publish in the future.

Co-authorship network of co-authors of Kenichi Kumatani

This figure shows the co-authorship network connecting the top 25 collaborators of Kenichi Kumatani. A scholar is included among the top collaborators of Kenichi Kumatani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kenichi Kumatani. Kenichi Kumatani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
14
2 2
3 21
4 25
5 7
6
Microphone array processing for distant speech recognition: Spherical arrays
4
7
Microphone array processing for distant speech recognition: Towards real-world deployment
27
8 80
9 1
10 2
11 8
12
Distant Speech Recognition: No Black Boxes Allowed
0
13 36
14 3
15
Maximum negentropy beamforming with superdirectivity
5
16 4
17
To separate speech: a system for recognizing simultaneous speech
19
18 13
19
Audio-Visual Speech Recognition Based on Optimized Product HMMs and GMM Based-MCE-GPD Stream Weight Estimation
2
20
An Adaptive Integration Method Based on Product HMM for Bi-Modal Speech Recognition
4

About Kenichi Kumatani

Kenichi Kumatani is a scholar working on Signal Processing, Computational Mechanics and Artificial Intelligence, having authored 39 papers that have together received 490 indexed citations. Recurring topics across this work include Speech and Audio Processing (36 papers), Advanced Adaptive Filtering Techniques (22 papers) and Speech Recognition and Synthesis (15 papers). The work is most often cited by research in Signal Processing (417 citations), Computational Mechanics (165 citations) and Artificial Intelligence (228 citations). Kenichi Kumatani has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include John McDonough, Bhiksha Raj, Dietrich Klakow, Minhua Wu, Nikko Ström, Weifeng Li, Philip N. Garner, Jill Fain Lehman, Matthias Wölfel and Rita Singh. Their work appears in journals such as IEEE Signal Processing Magazine, IEEE Transactions on Audio Speech and Language Processing and IEICE Transactions on Information and Systems.

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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