Yung‐Hwan Oh

494 citations
47 papers · 339 indexed · h-index 8
Topics
Speech and Audio Processing (26 papers)Speech Recognition and Synthesis (26 papers)Music and Audio Processing (11 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Yung‐Hwan Oh

43 papers receiving 304 citations

Peers

Yung‐Hwan Oh
Comparison fields: 5 of 47
  • Signal Processing 223
  • Artificial Intelligence 192
  • Experimental and Cognitive Psychology 97
  • Computer Vision and Pattern Recognition 63
  • Cognitive Neuroscience 26
Replace Shozo Makino with:
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Michael S. Scordilis United States
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Zexu Pan Singapore
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Yung‐Hwan Oh relative to Shozo Makino Japan Shozo Makino's profile →
Citations per field
00.5×1.5×
Shozo Makino · 1×
Citations per year

Countries citing papers authored by Yung‐Hwan Oh

Since Specialization
Citations

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

Fields of papers citing papers by Yung‐Hwan Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yung‐Hwan Oh. 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 Yung‐Hwan Oh. The network helps show where Yung‐Hwan Oh may publish in the future.

Co-authorship network of co-authors of Yung‐Hwan Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Yung‐Hwan Oh. A scholar is included among the top collaborators of Yung‐Hwan Oh 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 Yung‐Hwan Oh. Yung‐Hwan Oh 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
#WorkIndexed citations
1 1
2 1
3 3
4 8
5
Feature vector classification by threshold for speaker identification.
0
6
KEYWORD SPOTTING IN BROADCAST NEWS
2
7 4
8 6
9 27
10 2
11 2
12 1
13
Robust Speaker Identification using Independent Component Analysis
0
14 3
15 5
16 35
17
for Speech Recognition
6
18 1
19 2
20
Performance Improvement of Speaker Recongnition System for Small Training Data
3

About Yung‐Hwan Oh

Yung‐Hwan Oh is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 47 papers that have together received 339 indexed citations. Recurring topics across this work include Speech and Audio Processing (26 papers), Speech Recognition and Synthesis (26 papers) and Music and Audio Processing (11 papers). The work is most often cited by research in Signal Processing (223 citations), Experimental and Cognitive Psychology (97 citations) and Artificial Intelligence (192 citations). Yung‐Hwan Oh has collaborated with scholars based in South Korea and United States. Frequent co-authors include Jeong‐Sik Park, Ji‐Hwan Kim, Gil‐Jin Jang, Sangho Lee, Te-Won Lee, Ha-Jin Yu, Kyung-Mi Park, Sangho Lee, Sang-Ho Lee and Woo-Jin Han. Their work appears in journals such as Pattern Recognition, Neurocomputing and Electronics 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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