Yosuke Higuchi

738 total citations
22 papers, 448 citations indexed

About

Yosuke Higuchi is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yosuke Higuchi has authored 22 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 12 papers in Signal Processing and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Yosuke Higuchi's work include Speech Recognition and Synthesis (21 papers), Music and Audio Processing (12 papers) and Speech and Audio Processing (10 papers). Yosuke Higuchi is often cited by papers focused on Speech Recognition and Synthesis (21 papers), Music and Audio Processing (12 papers) and Speech and Audio Processing (10 papers). Yosuke Higuchi collaborates with scholars based in Japan, United States and China. Yosuke Higuchi's co-authors include Shinji Watanabe, Tetsunori Kobayashi, Tetsuji Ogawa, Hirofumi Inaguma, Nanxin Chen, Xuankai Chang, Chenda Li, Pengcheng Guo, Jing Shi and Tomoki Hayashi and has published in prestigious journals such as IEEE Journal of Selected Topics in Signal Processing, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) and 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

In The Last Decade

Yosuke Higuchi

21 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
Yosuke Higuchi Japan 11 417 247 35 18 12 22 448
Kai Feng Czechia 6 472 1.1× 396 1.6× 35 1.0× 28 1.6× 9 0.8× 9 518
Vitaly Lavrukhin United States 6 312 0.7× 214 0.9× 44 1.3× 15 0.8× 11 0.9× 20 371
Yatharth Saraf United States 9 385 0.9× 225 0.9× 57 1.6× 23 1.3× 5 0.4× 17 459
Zhehuai Chen United States 11 403 1.0× 214 0.9× 36 1.0× 17 0.9× 11 0.9× 41 443
Joel Pinto Switzerland 11 306 0.7× 240 1.0× 23 0.7× 27 1.5× 4 0.3× 24 344
Yannis Agiomyrgiannakis Greece 8 224 0.5× 199 0.8× 58 1.7× 13 0.7× 7 0.6× 18 307
Hossein Hadian Iran 8 296 0.7× 206 0.8× 30 0.9× 11 0.6× 6 0.5× 16 333
Takafumi Moriya Japan 10 255 0.6× 165 0.7× 17 0.5× 27 1.5× 14 1.2× 64 293
Rob Clark United States 7 479 1.1× 327 1.3× 64 1.8× 27 1.5× 5 0.4× 11 565
Jacob Kahn Israel 5 491 1.2× 280 1.1× 50 1.4× 25 1.4× 4 0.3× 5 536

Countries citing papers authored by Yosuke Higuchi

Since Specialization
Citations

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

Fields of papers citing papers by Yosuke Higuchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yosuke Higuchi

This figure shows the co-authorship network connecting the top 25 collaborators of Yosuke Higuchi. A scholar is included among the top collaborators of Yosuke Higuchi 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 Yosuke Higuchi. Yosuke Higuchi 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.
2.
Higuchi, Yosuke, et al.. (2023). Spotting Parodies: Detecting Alignment Collapse Between Lyrics and Singing Voice. 286–290. 1 indexed citations
3.
Dalmia, Siddharth, Yosuke Higuchi, Graham Neubig, et al.. (2023). CTC Alignments Improve Autoregressive Translation. 1623–1639. 18 indexed citations
4.
Peng, Yifan, Siddhant Arora, Yosuke Higuchi, et al.. (2023). A Study on the Integration of Pre-Trained SSL, ASR, LM and SLU Models for Spoken Language Understanding. 406–413. 9 indexed citations
5.
Higuchi, Yosuke, Andrew E. Rosenberg, Yuan Wang, Murali Karthick Baskar, & Bhuvana Ramabhadran. (2023). Mask-Conformer: Augmenting Conformer with Mask-Predict Decoder. 1–8. 1 indexed citations
6.
Higuchi, Yosuke, Tetsuji Ogawa, Tetsunori Kobayashi, & Shinji Watanabe. (2023). BECTRA: Transducer-Based End-To-End ASR with Bert-Enhanced Encoder. 1–5. 9 indexed citations
7.
Higuchi, Yosuke, Niko Moritz, Jonathan Le Roux, & Takaaki Hori. (2022). Momentum Pseudo-Labeling: Semi-Supervised ASR With Continuously Improving Pseudo-Labels. IEEE Journal of Selected Topics in Signal Processing. 16(6). 1424–1438. 10 indexed citations
8.
Higuchi, Yosuke, et al.. (2022). BERT Meets CTC: New Formulation of End-to-End Speech Recognition with Pre-trained Masked Language Model. 5486–5503. 14 indexed citations
9.
Higuchi, Yosuke, Niko Moritz, Jonathan Le Roux, & Takaaki Hori. (2022). Advancing Momentum Pseudo-Labeling with Conformer and Initialization Strategy. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7672–7676. 4 indexed citations
10.
Someki, Masao, Yosuke Higuchi, Tomoki Hayashi, & Shinji Watanabe. (2022). ESPnet-ONNX: Bridging a Gap Between Research and Production. 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). 420–427. 2 indexed citations
11.
Watanabe, Shinji, et al.. (2022). Improving Non-Autoregressive End-to-End Speech Recognition with Pre-Trained Acoustic and Language Models. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8522–8526. 17 indexed citations
12.
Higuchi, Yosuke, et al.. (2022). Hierarchical Conditional End-to-End ASR with CTC and Multi-Granular Subword Units. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7797–7801. 11 indexed citations
13.
Higuchi, Yosuke, Niko Moritz, Jonathan Le Roux, & Takaaki Hori. (2021). Momentum Pseudo-Labeling for Semi-Supervised Speech Recognition. 726–730. 20 indexed citations
14.
Guo, Pengcheng, Xuankai Chang, Tomoki Hayashi, et al.. (2021). Recent Developments on Espnet Toolkit Boosted By Conformer. 5874–5878. 149 indexed citations
15.
Inaguma, Hirofumi, Yosuke Higuchi, Kevin Duh, Tatsuya Kawahara, & Shinji Watanabe. (2021). ORTHROS: non-autoregressive end-to-end speech translation With dual-decoder. 7503–7507. 13 indexed citations
16.
Watanabe, Shinji, Xuankai Chang, Pengcheng Guo, et al.. (2021). The 2020 ESPnet Update: New Features, Broadened Applications, Performance Improvements, and Future Plans. 30. 1–6. 29 indexed citations
17.
Higuchi, Yosuke, Hirofumi Inaguma, Shinji Watanabe, Tetsuji Ogawa, & Tetsunori Kobayashi. (2021). Improved Mask-CTC for Non-Autoregressive End-to-End ASR. 8363–8367. 30 indexed citations
18.
Higuchi, Yosuke, Shinji Watanabe, Nanxin Chen, Tetsuji Ogawa, & Tetsunori Kobayashi. (2020). Mask CTC: Non-Autoregressive End-to-End ASR with CTC and Mask Predict. 3655–3659. 79 indexed citations
19.
Higuchi, Yosuke, Masayuki Suzuki, & Gakuto Kurata. (2020). Speaker Embeddings Incorporating Acoustic Conditions for Diarization. 7129–7133. 3 indexed citations
20.
Higuchi, Yosuke, Naohiro Tawara, Tetsunori Kobayashi, & Tetsuji Ogawa. (2019). Speaker Adversarial Training of DPGMM-Based Feature Extractor for Zero-Resource Languages. 266–270. 3 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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