Yusuke Yasuda

401 total citations
14 papers, 221 citations indexed

About

Yusuke Yasuda is a scholar working on Artificial Intelligence, Signal Processing and Computational Theory and Mathematics. According to data from OpenAlex, Yusuke Yasuda has authored 14 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 5 papers in Signal Processing and 1 paper in Computational Theory and Mathematics. Recurrent topics in Yusuke Yasuda's work include Speech Recognition and Synthesis (12 papers), Natural Language Processing Techniques (9 papers) and Speech and dialogue systems (4 papers). Yusuke Yasuda is often cited by papers focused on Speech Recognition and Synthesis (12 papers), Natural Language Processing Techniques (9 papers) and Speech and dialogue systems (4 papers). Yusuke Yasuda collaborates with scholars based in Japan, United Kingdom and United States. Yusuke Yasuda's co-authors include Junichi Yamagishi, Xin Wang, Erica Cooper, Cheng-I Lai, Shinji Takaki, Fuming Fang, Nanxin Chen and Tomoki Toda and has published in prestigious journals such as IEEE Access, IEEE Journal of Selected Topics in Signal Processing and Computer Speech & Language.

In The Last Decade

Yusuke Yasuda

12 papers receiving 200 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yusuke Yasuda Japan 7 200 136 15 12 6 14 221
Guoli Ye United States 10 208 1.0× 155 1.1× 9 0.6× 8 0.7× 4 0.7× 14 221
Puming Zhan United States 8 223 1.1× 148 1.1× 31 2.1× 15 1.3× 4 0.7× 19 246
Zhuoyuan Yao China 6 223 1.1× 164 1.2× 16 1.1× 12 1.0× 7 1.2× 6 239
Daisy Stanton United States 5 247 1.2× 142 1.0× 22 1.5× 10 0.8× 4 0.7× 6 265
Julián Salazar United States 5 158 0.8× 96 0.7× 25 1.7× 9 0.8× 4 0.7× 7 186
Shubham Toshniwal United States 7 216 1.1× 88 0.6× 13 0.9× 11 0.9× 3 0.5× 14 239
Tatiana Likhomanenko United States 4 151 0.8× 78 0.6× 24 1.6× 12 1.0× 3 0.5× 11 168
Yichong Leng China 5 120 0.6× 71 0.5× 26 1.7× 9 0.8× 5 0.8× 10 152
Julian Chan United States 8 204 1.0× 121 0.9× 15 1.0× 17 1.4× 2 0.3× 11 235
Jade Copet France 9 248 1.2× 121 0.9× 19 1.3× 24 2.0× 6 1.0× 12 269

Countries citing papers authored by Yusuke Yasuda

Since Specialization
Citations

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

Fields of papers citing papers by Yusuke Yasuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yusuke Yasuda

This figure shows the co-authorship network connecting the top 25 collaborators of Yusuke Yasuda. A scholar is included among the top collaborators of Yusuke Yasuda 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 Yusuke Yasuda. Yusuke Yasuda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Yasuda, Yusuke, et al.. (2024). Embedding Learning for Preference-based Speech Quality Assessment. 2685–2689.
2.
Yasuda, Yusuke & Tomoki Toda. (2023). Analysis of Mean Opinion Scores in Subjective Evaluation of Synthetic Speech Based on Tail Probabilities. 5491–5495. 3 indexed citations
3.
Yasuda, Yusuke, et al.. (2023). Preference-based training framework for automatic speech quality assessment using deep neural network. arXiv (Cornell University). 546–550. 2 indexed citations
4.
Yasuda, Yusuke & Tomoki Toda. (2022). Investigation of Japanese PnG BERT Language Model in Text-to-Speech Synthesis for Pitch Accent Language. IEEE Journal of Selected Topics in Signal Processing. 16(6). 1319–1328. 7 indexed citations
5.
Yasuda, Yusuke, et al.. (2021). End-to-End Text-to-Speech Using Latent Duration Based on VQ-VAE. 5694–5698. 7 indexed citations
6.
Yasuda, Yusuke. (2021). Lexical pitch accent and duration modeling for neural end-to-end text-to-speech synthesis. 1 indexed citations
7.
Yasuda, Yusuke, et al.. (2020). Modeling of Rakugo Speech and Its Limitations: Toward Speech Synthesis That Entertains Audiences. IEEE Access. 8. 138149–138161. 5 indexed citations
8.
Cooper, Erica, Cheng-I Lai, Yusuke Yasuda, et al.. (2020). Zero-Shot Multi-Speaker Text-To-Speech with State-Of-The-Art Neural Speaker Embeddings. 6184–6188. 98 indexed citations
9.
Yasuda, Yusuke, Xin Wang, & Junichi Yamagishi. (2020). Investigation of learning abilities on linguistic features in sequence-to-sequence text-to-speech synthesis. Computer Speech & Language. 67. 101183–101183. 13 indexed citations
11.
Cooper, Erica, Cheng-I Lai, Yusuke Yasuda, & Junichi Yamagishi. (2020). Can Speaker Augmentation Improve Multi-Speaker End-to-End TTS?. 3979–3983. 14 indexed citations
12.
Yasuda, Yusuke, Xin Wang, & Junichi Yamagishi. (2019). Initial investigation of encoder-decoder end-to-end TTS using marginalization of monotonic hard alignments. 211–216. 8 indexed citations
14.
Yasuda, Yusuke, Xin Wang, Shinji Takaki, & Junichi Yamagishi. (2019). Investigation of Enhanced Tacotron Text-to-speech Synthesis Systems with Self-attention for Pitch Accent Language. Edinburgh Research Explorer (University of Edinburgh). 6905–6909. 56 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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