Kenichi Kumatani

895 total citations
39 papers, 490 citations indexed

About

Kenichi Kumatani is a scholar working on Signal Processing, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Kenichi Kumatani has authored 39 papers receiving a total of 490 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Signal Processing, 22 papers in Computational Mechanics and 16 papers in Artificial Intelligence. Recurrent topics in Kenichi Kumatani's work include Speech and Audio Processing (36 papers), Advanced Adaptive Filtering Techniques (22 papers) and Speech Recognition and Synthesis (15 papers). Kenichi Kumatani is often cited by papers focused on Speech and Audio Processing (36 papers), Advanced Adaptive Filtering Techniques (22 papers) and Speech Recognition and Synthesis (15 papers). Kenichi Kumatani collaborates with scholars based in Germany, United States and Switzerland. Kenichi Kumatani's co-authors include John McDonough, Bhiksha Raj, Dietrich Klakow, Nikko Ström, Minhua Wu, Weifeng Li, Philip N. Garner, Jill Fain Lehman, Matthias Wölfel and Tobias Gehrig and has published in prestigious journals such as IEEE Signal Processing Magazine, IEEE Transactions on Audio Speech and Language Processing and IEICE Transactions on Information and Systems.

In The Last Decade

Kenichi Kumatani

36 papers receiving 432 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kenichi Kumatani Germany 14 417 228 165 73 43 39 490
Afsaneh Asaei Switzerland 14 366 0.9× 186 0.8× 160 1.0× 140 1.9× 57 1.3× 51 489
Marco Matassoni Italy 13 656 1.6× 441 1.9× 171 1.0× 104 1.4× 53 1.2× 65 764
Fotios Talantzis Greece 8 192 0.5× 83 0.4× 88 0.5× 62 0.8× 54 1.3× 22 258
Jeih-weih Hung Taiwan 12 464 1.1× 361 1.6× 106 0.6× 20 0.3× 76 1.8× 88 556
Yan-Hui Tu China 12 414 1.0× 270 1.2× 121 0.7× 40 0.5× 26 0.6× 29 497
Aditya Arie Nugraha Japan 10 617 1.5× 301 1.3× 206 1.2× 22 0.3× 44 1.0× 31 676
K. K. Chin Japan 10 426 1.0× 423 1.9× 71 0.4× 24 0.3× 34 0.8× 26 569
Alessio Brutti Italy 16 544 1.3× 187 0.8× 172 1.0× 205 2.8× 140 3.3× 72 686
Dongsuk Yook South Korea 10 221 0.5× 144 0.6× 34 0.2× 46 0.6× 53 1.2× 31 298

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
1.
Wang, Chengyi, Yu Wu, Yao Qian, et al.. (2021). UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data. International Conference on Machine Learning. 10937–10947. 14 indexed citations
2.
Dimitriadis, Dimitrios, Kenichi Kumatani, Yashesh Gaur, et al.. (2021). Ensemble Combination between Different Time Segmentations. 6768–6772. 2 indexed citations
3.
Dimitriadis, Dimitrios, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, & Şefik Emre Eskimez. (2020). A Federated Approach in Training Acoustic Models. 981–985. 21 indexed citations
4.
Wu, Minhua, Kenichi Kumatani, Shiva Sundaram, Nikko Ström, & Björn Hoffmeister. (2019). Frequency Domain Multi-channel Acoustic Modeling for Distant Speech Recognition. arXiv (Cornell University). 6640–6644. 25 indexed citations
5.
Kumatani, Kenichi, Kazumasa Yamamoto, John McDonough, et al.. (2012). Microphone array processing for distant speech recognition: Towards real-world deployment. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1–10. 27 indexed citations
6.
McDonough, John, Kenichi Kumatani, & Bhiksha Raj. (2012). Microphone array processing for distant speech recognition: Spherical arrays. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1–10. 4 indexed citations
7.
Kumatani, Kenichi, John McDonough, & Bhiksha Raj. (2012). Microphone Array Processing for Distant Speech Recognition: From Close-Talking Microphones to Far-Field Sensors. IEEE Signal Processing Magazine. 29(6). 127–140. 80 indexed citations
8.
Kumatani, Kenichi, Bhiksha Raj, Rita Singh, & John McDonough. (2012). Microphone array post-filter based on spatially-correlated noise measurements for distant speech recognition. 298–301. 11 indexed citations
9.
Kumatani, Kenichi, John McDonough, & Bhiksha Raj. (2011). Maximum kurtosis beamforming with a subspace filter for distant speech recognition. 179–184. 8 indexed citations
10.
Kumatani, Kenichi, John McDonough, Jill Fain Lehman, & Bhiksha Raj. (2011). Channel selection based on multichannel cross-correlation coefficients for distant speech recognition. 1–6. 36 indexed citations
11.
McDonough, John, Wei Chu, Kenichi Kumatani, Bhiksha Raj, & Jill Fain Lehman. (2011). An information filter for voice prompt suppression. 5. 321–325. 1 indexed citations
12.
McDonough, John, et al.. (2011). Distant Speech Recognition: No Black Boxes Allowed. 1–11.
13.
McDonough, John, Bhiksha Raj, & Kenichi Kumatani. (2011). On the combination of voice prompt suppression with maximum kurtosis beamforming. 25–28. 2 indexed citations
14.
Kumatani, Kenichi, Liang Lu, John McDonough, Arnab Ghoshal, & Dietrich Klakow. (2010). Maximum negentropy beamforming with superdirectivity. European Signal Processing Conference. 2067–2071. 5 indexed citations
15.
Kumatani, Kenichi, Hazım Kemal Ekenel, Hua Gao, Rainer Stiefelhagen, & Aytül Erçi̇l. (2008). Multi-stream gaussian mixture model based facial feature localization. Repository KITopen (Karlsruhe Institute of Technology). 2. 1–4. 4 indexed citations
16.
McDonough, John, Kenichi Kumatani, Tobias Gehrig, et al.. (2007). To separate speech: a system for recognizing simultaneous speech. Aviation Space and Environmental Medicine. 66(7). 283–294. 19 indexed citations
17.
Fügen, Christian, Matthias Wölfel, John McDonough, et al.. (2006). Advances in lecture recognition: the ISL RT-06s evaluation system. paper 1415–Tue3A2O.2. 13 indexed citations
18.
Kumatani, Kenichi. (2003). Audio-Visual Speech Recognition Based on Optimized Product HMMs and GMM Based-MCE-GPD Stream Weight Estimation. IEICE Transactions on Information and Systems. 86(3). 454–463. 2 indexed citations
19.
Nakamura, Satoshi, Kenichi Kumatani, & Shinichi Tamura. (2003). Multi-modal temporal asynchronicity modeling by product HMMs for robust audio-visual speech recognition. 305–309. 9 indexed citations
20.
Kumatani, Kenichi, Kiyohiro Shikano, & Satoshi Nakamura. (2001). An Adaptive Integration Method Based on Product HMM for Bi-Modal Speech Recognition. IPSJ SIG Notes. 2000(119). 67–72. 4 indexed citations

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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