Chia-Ping Chen

1.2k total citations
75 papers, 762 citations indexed

About

Chia-Ping Chen is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chia-Ping Chen has authored 75 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 37 papers in Signal Processing and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chia-Ping Chen's work include Speech Recognition and Synthesis (39 papers), Speech and Audio Processing (33 papers) and Music and Audio Processing (20 papers). Chia-Ping Chen is often cited by papers focused on Speech Recognition and Synthesis (39 papers), Speech and Audio Processing (33 papers) and Music and Audio Processing (20 papers). Chia-Ping Chen collaborates with scholars based in Taiwan, United States and China. Chia-Ping Chen's co-authors include Jeff Bilmes, Chu‐Song Chen, Hung-yi Lee, Lin-shan Lee, Katrin Kirchhoff, Yeong‐Cheng Liou, Yonghong Yao, Yuhao Huang, Ching-Feng Yeh and Yu-Lin Chang and has published in prestigious journals such as IEEE Access, Medicine and Industrial Marketing Management.

In The Last Decade

Chia-Ping Chen

67 papers receiving 704 citations

Peers

Chia-Ping Chen
Comparison fields: 5 of 92
  • Artificial Intelligence 421
  • Signal Processing 410
  • Computer Vision and Pattern Recognition 206
  • Experimental and Cognitive Psychology 77
  • Media Technology 33
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Citations per field, relative to Chia-Ping Chen
Chia-Ping Chen · 1×
Citations per year, relative to Chia-Ping Chen
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Countries citing papers authored by Chia-Ping Chen

Since Specialization
Citations

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

Fields of papers citing papers by Chia-Ping Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia-Ping Chen. 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 Chia-Ping Chen. The network helps show where Chia-Ping Chen may publish in the future.

Co-authorship network of co-authors of Chia-Ping Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Chia-Ping Chen. A scholar is included among the top collaborators of Chia-Ping Chen 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 Chia-Ping Chen. Chia-Ping Chen 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
# Work Indexed citations
1 2
2 0
3 33
4
Exploiting Low-Resource Code-Switching Data to Mandarin-English Speech Recognition Systems
1
5 20
6 5
7 21
8 6
9
Data-driven rescaled Teager energy cepstral coefficients for noise-robust speech recognition
0
10
Semantic Information and Derivation Rules for Robust Dialogue Act Detection in a Spoken Dialogue System
1
11 12
12 12
13
A hidden Markov model-based approach for emotional speech synthesis.
6
14
Noise-Robust Speech Features Based on Cepstral Time Coefficients
2
15
Automatic Learning of Context-Free Grammar.
2
16
The 4-Source Photometric Stereo Under General Unknown Lighting
1
17 4
18 153
19
An Approach to Using the Web as a Live Corpus for Spoken Transliteration Name Access
2
20 24

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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