Toshio Irino

2.5k citations
123 papers · 1.6k indexed · h-index 18

Toshio Irino

111 papers receiving 1.5k citations

Peers

Toshio Irino
Comparison fields: 5 of 84
  • Signal Processing 1.0k
  • Cognitive Neuroscience 649
  • Artificial Intelligence 565
  • Experimental and Cognitive Psychology 369
  • Biomedical Engineering 172
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Citations per field
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Citations per year

Countries citing papers authored by Toshio Irino

Since Specialization
Citations

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

Fields of papers citing papers by Toshio Irino

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Toshio Irino

This figure shows the co-authorship network connecting the top 25 collaborators of Toshio Irino. A scholar is included among the top collaborators of Toshio Irino 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 Toshio Irino. Toshio Irino 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 2
2 1
3
Implementation of hearing impairment simulator based on the gammachirp auditory filterbank and its educational application
1
4 3
5 9
6 0
7
Detecting child speaker based on auditory feature vectors for VTL estimation
1
8
An interference-free representation of group delay for periodic signals
2
9
Manual and Accelerometer Analysis of Head Nodding Patterns in Goal-oriented Dialogues
3
10
A bottom-up procedure to extract periodicity structure of voiced sounds and its application to represent and restoration of pathological voices.
1
11
Effects of spectral envelope representations on resynthesized speech quality
1
12
Aperiodicity extraction based on linear prediction and temporal axis warping using fundamental frequency information
0
13 5
14 104
15
Accuracy improvement in speech sound propagation measurement using logarithmic temporal manipulation
0
16
A Study of Talker Localization Based on Subband CSP Analysis
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17 39
18 13
19 3
20 2

About Toshio Irino

Toshio Irino is a scholar working on Signal Processing, Artificial Intelligence and Cognitive Neuroscience, having authored 123 papers that have together received 1.6k indexed citations. Recurring topics across this work include Speech and Audio Processing (85 papers), Speech Recognition and Synthesis (45 papers) and Hearing Loss and Rehabilitation (27 papers). The work is most often cited by research in Signal Processing (1.0k citations), Developmental Biology (78 citations) and Cognitive Neuroscience (649 citations). Toshio Irino has collaborated with scholars based in Japan, United Kingdom and Austria. Frequent co-authors include Roy D. Patterson, Hideki Kawahara, Hideki Banno, Masanori Morise, Tôru Takahashi, Tomohiro Nakatani, Ryuichi Nisimura, Masashi Unoki, Richard E. Turner and David R. Smith. Their work appears in journals such as Proceedings of the National Academy of Sciences, Scientific Reports and IEEE Transactions on Signal Processing.

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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