Eunwoo Song
- Artificial Intelligence top 2%
- Signal Processing top 1%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Co-authors
- Jae-Min KimRyuichi YamamotoHong-Goo KangJae‐Yoon SimFrank K. SoongHong-June ParkByung‐Ho NamHee‐Sug Ryu
- Topics
- Speech Recognition and Synthesis (29 papers)Speech and Audio Processing (27 papers)Music and Audio Processing (19 papers)
- Partner nations
- South KoreaJapanUnited States
In The Last Decade
Eunwoo Song
41 papers receiving 854 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 522
- Signal Processing 503
- Electrical and Electronic Engineering 120
- Computer Vision and Pattern Recognition 117
- Biomedical Engineering 108
Countries citing papers authored by Eunwoo Song
This map shows the geographic impact of Eunwoo Song'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 Eunwoo Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eunwoo Song more than expected).
Fields of papers citing papers by Eunwoo Song
This network shows the impact of papers produced by Eunwoo Song. 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 Eunwoo Song. The network helps show where Eunwoo Song may publish in the future.
Co-authorship network of co-authors of Eunwoo Song
This figure shows the co-authorship network connecting the top 25 collaborators of Eunwoo Song. A scholar is included among the top collaborators of Eunwoo Song 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 Eunwoo Song. Eunwoo Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 6 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 8 | |
| 7 | 12 | |
| 8 | Parallel Wavegan: A Fast Waveform Generation Model Based on Generative Adversarial Networks with Multi-Resolution Spectrogrambreakdown → | 462 |
| 9 | 4 | |
| 10 | ExcitGlow: Improving a WaveGlow-based Neural Vocoder with Linear Prediction Analysis | 3 |
| 11 | 18 | |
| 12 | Speaker-adaptive neural vocoders for statistical parametric speech synthesis systems. | 1 |
| 13 | 1 | |
| 14 | 2 | |
| 15 | 27 | |
| 16 | 74 | |
| 17 | 1 | |
| 18 | 74 | |
| 19 | 13 | |
| 20 | 3 |
About Eunwoo Song
Eunwoo Song is a scholar working on Signal Processing, Artificial Intelligence and Obstetrics and Gynecology, having authored 45 papers that have together received 896 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (29 papers), Speech and Audio Processing (27 papers) and Music and Audio Processing (19 papers). The work is most often cited by research in Signal Processing (503 citations), Artificial Intelligence (522 citations) and Obstetrics and Gynecology (84 citations). Eunwoo Song has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Jae-Min Kim, Ryuichi Yamamoto, Hong-Goo Kang, Jae‐Yoon Sim, Frank K. Soong, Hong-June Park, Byung‐Ho Nam, Hee‐Sug Ryu, Jae‐Weon Kim and Jinseob Kim. Their work appears in journals such as ACS Nano, Nature Biotechnology and British Journal of Cancer.
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.