Tomohiro Nakatani

9.3k total citations
330 papers, 6.2k citations indexed

About

Tomohiro Nakatani is a scholar working on Signal Processing, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Tomohiro Nakatani has authored 330 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 292 papers in Signal Processing, 158 papers in Artificial Intelligence and 123 papers in Computational Mechanics. Recurrent topics in Tomohiro Nakatani's work include Speech and Audio Processing (283 papers), Speech Recognition and Synthesis (150 papers) and Music and Audio Processing (122 papers). Tomohiro Nakatani is often cited by papers focused on Speech and Audio Processing (283 papers), Speech Recognition and Synthesis (150 papers) and Music and Audio Processing (122 papers). Tomohiro Nakatani collaborates with scholars based in Japan, United States and Germany. Tomohiro Nakatani's co-authors include Keisuke Kinoshita, Marc Delcroix, Takuya Yoshioka, Shoko Araki, Nobutaka Ito, Masato Miyoshi, Atsunori Ogawa, Masakiyo Fujimoto, Takuya Higuchi and Shinji Watanabe and has published in prestigious journals such as Proceedings of the IEEE, Spine and IEEE Transactions on Signal Processing.

In The Last Decade

Tomohiro Nakatani

306 papers receiving 5.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomohiro Nakatani Japan 40 5.5k 3.1k 2.2k 743 355 330 6.2k
Li-Rong Dai China 34 4.3k 0.8× 3.8k 1.2× 1.1k 0.5× 576 0.8× 151 0.4× 323 5.9k
Nobutaka Ono Japan 30 2.8k 0.5× 524 0.2× 1.3k 0.6× 232 0.3× 197 0.6× 263 3.4k
Nam Soo Kim South Korea 23 2.3k 0.4× 1.3k 0.4× 991 0.5× 267 0.4× 113 0.3× 181 2.8k
Ian McLoughlin Singapore 23 1.5k 0.3× 1.1k 0.4× 87 0.0× 241 0.3× 221 0.6× 228 2.7k
Peter Vary Germany 32 3.5k 0.6× 943 0.3× 2.3k 1.1× 980 1.3× 497 1.4× 302 4.6k
Takuya Yoshioka Japan 33 4.7k 0.8× 3.3k 1.1× 1.4k 0.7× 542 0.7× 234 0.7× 150 5.3k
Hiroshi Saruwatari Japan 31 4.2k 0.8× 1.8k 0.6× 2.0k 0.9× 394 0.5× 335 0.9× 484 4.9k
Richard C. Hendriks Netherlands 23 4.1k 0.7× 1.3k 0.4× 2.4k 1.1× 1.5k 2.0× 545 1.5× 134 4.6k
Rainer Martin Germany 28 3.9k 0.7× 1.0k 0.3× 2.7k 1.2× 1.1k 1.4× 446 1.3× 178 4.3k
Yi Hu United States 20 3.4k 0.6× 940 0.3× 2.0k 0.9× 1.3k 1.7× 467 1.3× 61 3.9k

Countries citing papers authored by Tomohiro Nakatani

Since Specialization
Citations

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

Fields of papers citing papers by Tomohiro Nakatani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomohiro Nakatani

This figure shows the co-authorship network connecting the top 25 collaborators of Tomohiro Nakatani. A scholar is included among the top collaborators of Tomohiro Nakatani 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 Tomohiro Nakatani. Tomohiro Nakatani 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.
Delcroix, Marc, et al.. (2025). SoundBeam meets M2D: Target Sound Extraction with Audio Foundation Model. 1–5. 2 indexed citations
2.
Nakatani, Tomohiro, et al.. (2024). DOA-informed switching independent vector extraction and beamforming for speech enhancement in underdetermined situations. EURASIP Journal on Audio Speech and Music Processing. 2024(1).
3.
Kamo, Naoyuki, et al.. (2024). Ensemble Inference for Diffusion Model-Based Speech Enhancement. 735–739. 2 indexed citations
4.
Nakatani, Tomohiro, et al.. (2024). Blind and Spatially-Regularized Online Joint Optimization of Source Separation, Dereverberation, and Noise Reduction. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 1157–1172. 5 indexed citations
5.
Kamo, Naoyuki, Marc Delcroix, & Tomohiro Nakatani. (2023). Target Speech Extraction with Conditional Diffusion Model. 176–180. 11 indexed citations
6.
Kawakami, Mamoru, Masatoshi Teraguchi, Ryohei Kagotani, et al.. (2019). Supervised physical therapy vs. home exercise for patients with lumbar spinal stenosis: a randomized controlled trial. The Spine Journal. 19(8). 1310–1318. 39 indexed citations
7.
Ochiai, Tsubasa, Marc Delcroix, Keisuke Kinoshita, Atsunori Ogawa, & Tomohiro Nakatani. (2019). Multimodal SpeakerBeam: Single Channel Target Speech Extraction with Audio-Visual Speaker Clues. 2718–2722. 33 indexed citations
8.
Delcroix, Marc, Keisuke Kinoshita, Atsunori Ogawa, Christian Huemmer, & Tomohiro Nakatani. (2018). Context Adaptive Neural Network Based Acoustic Models for Rapid Adaptation. IEEE/ACM Transactions on Audio Speech and Language Processing. 26(5). 895–908. 10 indexed citations
9.
10.
Žmolíková, Kateřina, Marc Delcroix, Keisuke Kinoshita, et al.. (2017). Speaker-Aware Neural Network Based Beamformer for Speaker Extraction in Speech Mixtures. 2655–2659. 67 indexed citations
11.
Araki, Shoko, Masakiyo Fujimoto, Takuya Yoshioka, et al.. (2015). Deep Learning Based Distant-talking Speech Processing in Real-world Sound Environments. NTT technical review. 13(11). 19–24. 2 indexed citations
12.
Yoshioka, Takuya, Shigeki Karita, & Tomohiro Nakatani. (2015). Far-field speech recognition using CNN-DNN-HMM with convolution in time. 4360–4364. 22 indexed citations
13.
Yoshioka, Takuya & Tomohiro Nakatani. (2013). Dereverberation for reverberation-robust microphone arrays. European Signal Processing Conference. 1–5. 24 indexed citations
14.
Delcroix, Marc, Atsunori Ogawa, Shinji Watanabe, Tomohiro Nakatani, & Atsushi Nakamura. (2012). Discriminative feature transforms using differenced maximum mutual information. 4753–4756. 2 indexed citations
15.
Nakatani, Tomohiro, et al.. (2008). A Game Recommendation System Based on Classification of Experimential Value. 2008(129). 49–56.
16.
Ishizuka, Kentaro & Tomohiro Nakatani. (2006). Study of Noise Robust Voice Activity Detection Based on Periodic Component to Aperiodic Component Ratio. Conference of the International Speech Communication Association. 65–70. 22 indexed citations
17.
Nakatani, Tomohiro, Hiroshi G. Okuno, Masataka Goto, & Takatoshi Ito. (1998). Multiagent based binaural sound stream segregation. 195–214. 10 indexed citations
18.
Nakatani, Tomohiro & Hiroshi G. Okuno. (1998). Sound ontology for computational auditory scence analysis. National Conference on Artificial Intelligence. 1004–1010. 8 indexed citations
19.
Nakatani, Tomohiro, Hiroshi G. Okuno, & Takeshi Kawabata. (1995). Residue-driven architecture for computational auditory scene analysis. International Joint Conference on Artificial Intelligence. 165–172. 24 indexed citations
20.
Nakatani, Tomohiro, Hiroshi G. Okuno, & Takeshi Kawabata. (1994). Auditory stream segregation in auditory scene analysis with a multi-agent system. National Conference on Artificial Intelligence. 100–107. 18 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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