Eric Chang

7.0k citations
96 papers · 4.1k indexed · h-index 34

Eric Chang

95 papers receiving 3.9k citations

Peers

Eric Chang
Comparison fields: 5 of 166
  • Artificial Intelligence 2.3k
  • Signal Processing 713
  • Computer Vision and Pattern Recognition 1.2k
  • Transportation 302
  • Computational Mathematics 21
Replace Junping Zhang with:
Junping Zhang China
Zhanyu Ma China
S. Lecœuche France
Shaozi Li China
Mu Li China
Xiaodan Liang China
Xin Ning China
Adel Elmaghraby United States
Irfan Mehmood South Korea
Eric Chang relative to Junping Zhang China Junping Zhang's profile →
Citations per field
00.5×2.7×
Junping Zhang · 1×
Citations per year

Countries citing papers authored by Eric Chang

Since Specialization
Citations

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

Fields of papers citing papers by Eric Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Eric Chang, 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 Eric Chang Line = papers co-authored together Eric Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20221
3 20203
4 2020100
5 202076
6 20195
7 201940
8 201859
9 2017289
10 201717
11 20149
12 201328
13 20135
14 201352
15
A concatenative Mandarin TTS system without prosody model and prosody modification.
200114
16 200060
17
Using Voice Transformations to Create Additional Training Talkers for Word Spotting
19946
18
Figure of Merit Training for Detection and Spotting
19936
19
A Boundary Hunting Radial Basis Function Classifier which Allocates Centers Constructively
199213
20
Using Genetic Algorithms to Improve Pattern Classification Performance
199056

About Eric Chang

Eric Chang is a scholar working on Signal Processing, Artificial Intelligence, Computational Mathematics, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 96 papers that have together received 4.1k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (37 papers), Speech and Audio Processing (25 papers), Natural Language Processing Techniques (21 papers), Topic Modeling (15 papers), AI in cancer detection (14 papers), Music and Audio Processing (13 papers), Speech and dialogue systems (11 papers) and Image Retrieval and Classification Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (2.3k citations), Signal Processing (713 citations), Computer Vision and Pattern Recognition (1.2k citations), Transportation (302 citations) and Computational Mathematics (21 citations). Eric Chang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yan Xu, Maode Lai, Yu Zheng, Zhuowen Tu, Jun-Yan Zhu, Yubo Fan, Chao Huang, Richard P. Lippmann, Zhipeng Jia and Yuqing Ai. Their work appears in journals such as BMC Bioinformatics, Journal of the American Medical Informatics Association, PLoS ONE, Medical Image Analysis and Scientific Reports.

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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