Chi-Chun Lee
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- Emotion and Mood Recognition 81
- Signal Processing top 0.2%
- Speech and Audio Processing 42
- Music and Audio Processing 33
- Artificial Intelligence top 0.5%
- Speech Recognition and Synthesis 29
- Sentiment Analysis and Opinion Mining 17
- Cognitive Neuroscience top 2%
- Autism Spectrum Disorder Research 19
- EEG and Brain-Computer Interfaces 9
- Pharmacy top 1%
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- Digital Imaging for Blood Diseases 9
Chi-Chun Lee
176 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Experimental and Cognitive Psychology 2.8k
- Signal Processing 1.7k
- Artificial Intelligence 2.3k
- Cognitive Neuroscience 718
- Pharmacy 171
Countries citing papers authored by Chi-Chun Lee
This map shows the geographic impact of Chi-Chun Lee'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 Chi-Chun Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi-Chun Lee more than expected).
Fields of papers citing papers by Chi-Chun Lee
This network shows the impact of papers produced by Chi-Chun Lee. 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 Chi-Chun Lee. The network helps show where Chi-Chun Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chi-Chun Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 0 | |
| 7 | 2024 | 5 | |
| 8 | 2024 | 3 | |
| 9 | 2024 | 1 | |
| 10 | 2023 | 1 | |
| 11 | 2021 | 26 | |
| 12 | Sensing with Contexts: Crying Reason Classification for Infant Care Center with Environmental Fusion | 2020 | 1 |
| 13 | “Your Behavior Makes Me Think It Is a Lie”: Recognizing Perceived Deception using Multimodal Data in Dialog Games | 2020 | 2 |
| 14 | 2018 | 64 | |
| 15 | 2017 | 25 | |
| 16 | 2017 | 1 | |
| 17 | 2017 | 1 | |
| 18 | 2017 | 10 | |
| 19 | 2012 | 45 | |
| 20 | Using measures of vocal entrainment to inform outcome-related behaviors in marital conflicts | 2012 | 3 |
About Chi-Chun Lee
Chi-Chun Lee is a scholar working on Experimental and Cognitive Psychology, Signal Processing and Artificial Intelligence, having authored 195 papers that have together received 4.8k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (81 papers), Speech and Audio Processing (42 papers), Music and Audio Processing (33 papers), Speech Recognition and Synthesis (29 papers), Autism Spectrum Disorder Research (19 papers), Sentiment Analysis and Opinion Mining (17 papers), Digital Imaging for Blood Diseases (9 papers) and EEG and Brain-Computer Interfaces (9 papers). The work is most often cited by research in Experimental and Cognitive Psychology (2.8k citations), Signal Processing (1.7k citations) and Artificial Intelligence (2.3k citations). Chi-Chun Lee has collaborated with scholars based in Taiwan, United States and Australia. Frequent co-authors include Shrikanth Narayanan, Carlos Busso, Sungbok Lee, Emily Mower, Abe Kazemzadeh, Murtaza Bulut, Samuel Kim, Daniel Bone, Matthew Black and Panayiotis Georgiou. Their work appears in journals such as IEEE Transactions on Affective Computing, International Polymer Processing, Blood, IEEE Signal Processing Magazine and IEEE Journal of Biomedical and Health Informatics.
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.