James Qin

6.4k citations
9 papers · 2.1k · 1 hit paper · h-index 7

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech and dialogue systems

Papers in

    • Speech Recognition and Synthesis 8
    • Natural Language Processing Techniques 2
    • Topic Modeling 2
    • Algorithms and Data Compression 1
    • Speech and Audio Processing 6
    • Music and Audio Processing 5

James Qin

9 papers receiving 2.0k citations

James Qin's Hit Papers

Conformer: Convolution-augmented Transformer for Speech Recognition 2020 · 1.7k citations
1.7k0+2+4Years since publication50010001.5k

Peers

James Qin
Comparison fields: 5 of 103
  • Signal Processing 1.2k
  • Artificial Intelligence 1.7k
  • Computer Vision and Pattern Recognition 290
  • Experimental and Cognitive Psychology 100
  • Developmental Biology 11
Replace Anmol Gulati with:
Anmol Gulati United States
Niki Parmar United States
George Saon United States
Jui-Ting Huang United States
Xiaodong Cui United States
Hagen Soltau United States
Maurizio Omologo Italy
Yanmin Qian China
James Qin relative to Anmol Gulati United States Anmol Gulati's profile →
Citations per field
00.5×1.5×
Anmol Gulati · 1×
Citations per year

Countries citing papers authored by James Qin

Since Specialization
Citations

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

Fields of papers citing papers by James Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
Conformer: Convolution-augmented Transformer for Speech Recognition
Hit paper breakdown →
20201668
2 2021168
3 2020162
4 202167
5 202141
6 202131
7 202010
8 20242
9 20241

About James Qin

James Qin is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Information Systems and Infectious Diseases, having authored 9 papers that have together received 2.1k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (8 papers), Speech and Audio Processing (6 papers), Music and Audio Processing (5 papers), Natural Language Processing Techniques (2 papers), Topic Modeling (2 papers), Caching and Content Delivery (1 paper), Recommender Systems and Techniques (1 paper) and Algorithms and Data Compression (1 paper). The work is most often cited by research in Signal Processing (1.2k citations), Artificial Intelligence (1.7k citations), Computer Vision and Pattern Recognition (290 citations), Experimental and Cognitive Psychology (100 citations) and Developmental Biology (11 citations). James Qin has collaborated with scholars based in United States. Frequent co-authors include Ruoming Pang, Chung‐Cheng Chiu, Wei Han, Yu Zhang, Yonghui Wu, Anmol Gulati, Jiahui Yu, Niki Parmar, Shibo Wang and Zhengdong Zhang.

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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