Toru Nakashika
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 10%
- Physiology
- Experimental and Cognitive Psychology
- Co-authors
- Tetsuya TakiguchiYasuo ArikiRyoichi TakashimaYasuhiro MinamiRyo AiharaChristophe GarcíaShinji TakakiYuki Takashima
- Topics
- Speech and Audio Processing (33 papers)Speech Recognition and Synthesis (28 papers)Music and Audio Processing (27 papers)
- Journals
- Applied SciencesIEEE/ACM Transactions on Audio Speech and Language ProcessingIEICE Transactions on Information and Systems
- Partner nations
- JapanMexicoUnited Kingdom
In The Last Decade
Toru Nakashika
41 papers receiving 364 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 344
- Signal Processing 337
- Computer Vision and Pattern Recognition 71
- Physiology 46
- Experimental and Cognitive Psychology 20
Countries citing papers authored by Toru Nakashika
This map shows the geographic impact of Toru Nakashika'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 Toru Nakashika with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toru Nakashika more than expected).
Fields of papers citing papers by Toru Nakashika
This network shows the impact of papers produced by Toru Nakashika. 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 Toru Nakashika. The network helps show where Toru Nakashika may publish in the future.
Co-authorship network of co-authors of Toru Nakashika
This figure shows the co-authorship network connecting the top 25 collaborators of Toru Nakashika. A scholar is included among the top collaborators of Toru Nakashika 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 Toru Nakashika. Toru Nakashika is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 4 | |
| 9 | 14 | |
| 10 | 23 | |
| 11 | 8 | |
| 12 | DEPTH SPATIAL PYRAMID: A POOLING METHOD FOR 3D-OBJECT RECOGNITION | 0 |
| 13 | 47 | |
| 14 | 3 | |
| 15 | 25 | |
| 16 | Speaker-dependent conditional restricted Boltzmann machine for voice conversion | 1 |
| 17 | 87 | |
| 18 | 1 | |
| 19 | Iterative basis generation and supervised non-negative matrix factorization for signal analysis | 1 |
| 20 | Mathematical modeling of harmonic-timbre structure with multi-beta-distribution | 0 |
About Toru Nakashika
Toru Nakashika is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 45 papers that have together received 413 indexed citations. Recurring topics across this work include Speech and Audio Processing (33 papers), Speech Recognition and Synthesis (28 papers) and Music and Audio Processing (27 papers). The work is most often cited by research in Signal Processing (337 citations), Artificial Intelligence (344 citations) and Computer Vision and Pattern Recognition (71 citations). Toru Nakashika has collaborated with scholars based in Japan, Mexico and United Kingdom. Frequent co-authors include Tetsuya Takiguchi, Yasuo Ariki, Ryoichi Takashima, Yasuhiro Minami, Ryo Aihara, Christophe García, Shinji Takaki, Yuki Takashima, Junichi Yamagishi and Xin Wang. Their work appears in journals such as Applied Sciences, IEEE/ACM 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.