Chenchen Ding

724 citations
45 papers · 313 · h-index 10

Impact in

Papers in

Chenchen Ding

43 papers receiving 285 citations

Peers

Chenchen Ding
Comparison fields: 5 of 36
  • Artificial Intelligence 288
  • Computer Vision and Pattern Recognition 80
  • Signal Processing 30
  • Language and Linguistics 28
  • Experimental and Cognitive Psychology 21
Replace Mohammed Alhazmi with:
Mohammed Alhazmi Saudi Arabia
Adriana Stan Romania
Mourad Abbas Algeria
Ciro Martins Portugal
Siddharth Dalmia United States
Sebastian Stüker Germany
Markus Müller Germany
Win Pa Pa Myanmar
Wai-Kit Lo Hong Kong
Fethi Bougares France
Chenchen Ding relative to Mohammed Alhazmi Saudi Arabia Mohammed Alhazmi's profile →
Citations per field
00.5×8.7×
Mohammed Alhazmi · 1×
Citations per year

Countries citing papers authored by Chenchen Ding

Since Specialization
Citations

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

Fields of papers citing papers by Chenchen Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201639
2 202134
3 201927
4 201821
5 201919
6 201616
7 202014
8 202014
9 202012
10 201910
11 20218
12
Proceedings of the 3rd Workshop on Asian Translation (WAT2016)
20168
13 20236
14
Empirical Dependency-Based Head Finalization for Statistical Chinese-, English-, and French-to-Myanmar (Burmese) Machine Translation
20146
15 20205
16 20205
17 20205
18 20234
19
English-Myanmar NMT and SMT with Pre-ordering: NICT's Machine Translation Systems at WAT-2018.
20184
20 20164

About Chenchen Ding

Chenchen Ding is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Language and Linguistics, Signal Processing and Experimental and Cognitive Psychology, having authored 45 papers that have together received 313 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (33 papers), Topic Modeling (31 papers), Speech Recognition and Synthesis (14 papers), Translation Studies and Practices (6 papers), Multimodal Machine Learning Applications (5 papers), Phonetics and Phonology Research (4 papers), Speech and dialogue systems (4 papers) and Speech and Audio Processing (3 papers). The work is most often cited by research in Artificial Intelligence (288 citations), Computer Vision and Pattern Recognition (80 citations), Signal Processing (30 citations), Language and Linguistics (28 citations) and Experimental and Cognitive Psychology (21 citations). Chenchen Ding has collaborated with scholars based in Japan, Myanmar and China. Frequent co-authors include Masao Utiyama, Eiichiro Sumita, Sheng Li, Win Pa Pa, Raj Dabre, Longbiao Wang, Jianwu Dang, Isao Goto, Sadao Kurohashi and Toshiaki Nakazawa. Their work appears in journals such as Communications Materials, Speech Communication, Language Resources and Evaluation, IEEE/ACM Transactions on Audio Speech and Language Processing and ACM Transactions on Asian and Low-Resource Language Information Processing.

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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