Tetsuji Ogawa

945 total citations
98 papers, 581 citations indexed

About

Tetsuji Ogawa is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Tetsuji Ogawa has authored 98 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 52 papers in Signal Processing and 14 papers in Computer Vision and Pattern Recognition. Recurrent topics in Tetsuji Ogawa's work include Speech and Audio Processing (49 papers), Speech Recognition and Synthesis (45 papers) and Music and Audio Processing (23 papers). Tetsuji Ogawa is often cited by papers focused on Speech and Audio Processing (49 papers), Speech Recognition and Synthesis (45 papers) and Music and Audio Processing (23 papers). Tetsuji Ogawa collaborates with scholars based in Japan, United States and Egypt. Tetsuji Ogawa's co-authors include Tetsunori Kobayashi, Shinji Watanabe, Yosuke Higuchi, Naohiro Tawara, Walid Gomaa, Nanxin Chen, Hynek Heřmanský, Sri Harish Mallidi, Masahiro Murakawa and Jun Ogata and has published in prestigious journals such as IEEE Access, IEEE Sensors Journal and IEEE/ACM Transactions on Audio Speech and Language Processing.

In The Last Decade

Tetsuji Ogawa

84 papers receiving 550 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tetsuji Ogawa Japan	13	352	309	112	52	46	98	581
Dimitrios Dimitriadis United States	18	569 1.6×	473 1.5×	92 0.8×	54 1.0×	25 0.5×	57	813
Naoya Takahashi Japan	9	253 0.7×	492 1.6×	182 1.6×	39 0.8×	12 0.3×	28	620
Zhanjiang Song China	8	272 0.8×	329 1.1×	124 1.1×	9 0.2×	19 0.4×	18	546
Jürgen T. Geiger Germany	14	438 1.2×	538 1.7×	279 2.5×	46 0.9×	12 0.3×	35	895
Gordon Wichern United States	13	245 0.7×	396 1.3×	165 1.5×	74 1.4×	15 0.3×	79	567
Liang He China	17	484 1.4×	402 1.3×	102 0.9×	21 0.4×	18 0.4×	102	794
Cássia Valentini Botinhão United Kingdom	4	114 0.3×	118 0.4×	65 0.6×	35 0.7×	14 0.3×	8	318
Αλεξάνδρα Ψαρρού United Kingdom	11	118 0.3×	84 0.3×	448 4.0×	28 0.5×	47 1.0×	55	608
Yuki Mitsufuji Japan	14	310 0.9×	724 2.3×	181 1.6×	151 2.9×	12 0.3×	65	836
Hisashi Kawai Japan	15	746 2.1×	640 2.1×	145 1.3×	101 1.9×	57 1.2×	127	978

Countries citing papers authored by Tetsuji Ogawa

Since Specialization

Citations

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

Fields of papers citing papers by Tetsuji Ogawa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tetsuji Ogawa

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

All Works

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20 of 20 papers shown

Ogawa, Tetsuji, et al.. (2025). A Comparative Study on Positional Encoding for Time-Frequency Domain Dual-Path Transformer-Based Source Separation Models. 446–450.

Higuchi, Yosuke, et al.. (2024). Parody Detection Using Source-Target Attention with Teacher-Forced Lyrics. 1151–1155.

Herman, Jacob J., et al.. (2023). A Lightweight Transfer Learning-Based Model for Building Classification in Aerial Imagery. 38. 181–186. 3 indexed citations

Saito, Susumu, et al.. (2021). VocalTurk: Exploring Feasibility of Crowdsourced Speaker Identification. 1723–1727. 3 indexed citations

Kobayashi, Tetsunori, et al.. (2020). Efficient Human-In-The-Loop Object Detection using Bi-Directional Deep SORT and Annotation-Free Segment Identification. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1226–1233. 1 indexed citations

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

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

Kobayashi, Tetsunori, et al.. (2019). Data Assimilation Versus Machine Learning: Comparative Study Of Fish Catch Forecasting. OCEANS 2019 - Marseille. 3. 1–5.

Tawara, Naohiro, et al.. (2018). Sequential Fish Catch Forecasting Using Bayesian State Space Models. 3. 776–781. 5 indexed citations

10.

Ogawa, Tetsuji, et al.. (2017). Roles of ICT in Social Innovation: A Comparative Study for Social Innovation Based on Business Process Perspective. 25(4). 292.

11.

Ogawa, Tetsuji, Sri Harish Mallidi, Emmanuel Dupoux, et al.. (2016). A new efficient measure for accuracy prediction and its application to multistream-based unsupervised adaptation. 2222–2227. 1 indexed citations

12.

Tawara, Naohiro, Tetsuji Ogawa, Shinji Watanabe, & Tetsunori Kobayashi. (2016). Nested Gibbs sampling for mixture-of-mixture model and its application to speaker clustering. APSIPA Transactions on Signal and Information Processing. 5(1). 1 indexed citations

13.

Ogawa, Tetsuji & Tomoko Matsui. (2013). Machine learning for speaker recognition. Nippon Onkyo Gakkaishi/Acoustical science and technology/Nihon Onkyo Gakkaishi. 69(7). 349–356. 1 indexed citations

14.

Tawara, Naohiro, Tetsuji Ogawa, Shinji Watanabe, & Tetsunori Kobayashi. (2012). Fully Bayesian inference of multi-mixture Gaussian model and its evaluation using speaker clustering. 5253–5256. 5 indexed citations

15.

Tamura, Satoshi, Chiyomi Miyajima, Norihide Kitaoka, et al.. (2010). CENSREC-1-AV: an audio-visual corpus for noisy bimodal speech recognition.. AVSP. 6. 26 indexed citations

16.

Tanaka, Nobuaki, Tetsuji Ogawa, Kenzo Akagiri, & Tetsunori Kobayashi. (2010). Development of zonal beamformer and its application to robot audition. European Signal Processing Conference. 1529–1533. 3 indexed citations

17.

Yamada, Kei, et al.. (2010). Toward Developing Practical Automatic Speech Recognition Technology : Sound Source Separation Using Square Microphone Array. 51(11). 1410–1416.

18.

Kitaoka, Norihide, Takeshi Yamada, Chiyomi Miyajima, et al.. (2009). CENSREC-1-C: An evaluation framework for voice activity detection under noisy environments. Nippon Onkyo Gakkaishi/Acoustical science and technology/Nihon Onkyo Gakkaishi. 30(5). 363–371. 22 indexed citations

19.

Ogawa, Tetsuji, Hirofumi Takeuchi, Shintaro Takada, Kenzo Akagiri, & Tetsunori Kobayashi. (2008). Ears of the robot: Noise reduction using four-line ultra-micro omni-directional microphones mounted on a robot head. 1–5. 3 indexed citations

20.

Kitaoka, Norihide, Takeshi Yamada, Tetsuya Takiguchi, et al.. (2006). Progress Report of SLP Noisy Speech Recognition Evaluation WG : Individual evaluation framework for each factor affecting recognition performance (2). IEICE technical report. Speech. 106(405). 1–6. 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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