Joon Son Chung

10.3k citations
64 papers · 3.6k indexed · 5 hit papers · h-index 17

Joon Son Chung

59 papers receiving 3.5k citations

Hit Papers

AASIST: Audio Anti-Spoofing Using Integrate...15620182026202020234008001.2k

Peers

Joon Son Chung
Comparison fields: 5 of 89
  • Signal Processing 2.8k
  • Artificial Intelligence 2.4k
  • Computer Vision and Pattern Recognition 1.0k
  • Human-Computer Interaction 83
  • Experimental and Cognitive Psychology 119
Replace Guillaume Gravier with:
Guillaume Gravier France
Zhen-Hua Ling China
Dan Ellis United States
S. R. Mahadeva Prasanna India
Nicholas Evans France
Tomi Kinnunen Finland
Zhiyao Duan United States
Gerasimos Potamianos United States
Yifan Gong United States
Lie Lu China
Joon Son Chung relative to Guillaume Gravier France Guillaume Gravier's profile →
Citations per field
00.5×10×15×18.8×
Guillaume Gravier · 1×
Citations per year

Countries citing papers authored by Joon Son Chung

Since Specialization
Citations

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

Fields of papers citing papers by Joon Son Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joon Son Chung. 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 Joon Son Chung. The network helps show where Joon Son Chung may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Joon Son Chung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Joon Son Chung Line = papers co-authored together Joon Son Chung links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20261
2 20250
3 20252
4 20250
5 20250
6 20251
7 202410
8 20242
9 202411
10 20243
11 20231
12 20231
13
Playing a part: speaker verification at the movies
202112
14 20219
15 202070
16
In Defence of Metric Learning for Speaker Recognitionbreakdown →
2020232
17 202044
18 201925
19
VoxCeleb2: Deep Speaker Recognitionbreakdown →
20181248
20
The conversation: deep audio-visual speech enhancement
2018218

About Joon Son Chung

Joon Son Chung is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 64 papers that have together received 3.6k indexed citations. Recurring topics across this work include Speech and Audio Processing (44 papers), Speech Recognition and Synthesis (37 papers), Music and Audio Processing (34 papers), Face recognition and analysis (8 papers), Video Analysis and Summarization (6 papers), Natural Language Processing Techniques (6 papers), Speech and dialogue systems (4 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Signal Processing (2.8k citations), Artificial Intelligence (2.4k citations) and Computer Vision and Pattern Recognition (1.0k citations). Joon Son Chung has collaborated with scholars based in South Korea, United Kingdom and United States. Frequent co-authors include Andrew Zisserman, Arsha Nagrani, Triantafyllos Afouras, Weidi Xie, Andrew Senior, Oriol Vinyals, Bong‐Jin Lee, Jaesung Huh, Soo-Whan Chung and Hong-Goo Kang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Signal Processing Letters.

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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