Po-Han Chi

1.8k citations
3 papers · 527 · 1 hit paper · h-index 2

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech and dialogue systems
    • Sentiment Analysis and Opinion Mining

Papers in

    • Topic Modeling 3
    • Natural Language Processing Techniques 2
    • Speech Recognition and Synthesis 2
    • Machine Learning and Data Classification 1
    • Music and Audio Processing 1

Po-Han Chi

3 papers receiving 506 citations

Po-Han Chi's Hit Papers

SUPERB: Speech Processing Universal PERformance Benchmark 2021 · 409 citations
4090+1+3Years since publication100200300400

Peers

Po-Han Chi
Comparison fields: 5 of 53
  • Signal Processing 293
  • Artificial Intelligence 439
  • Experimental and Cognitive Psychology 69
  • Computer Vision and Pattern Recognition 42
  • Developmental Biology 4
Replace Andy T. Liu with:
Andy T. Liu Taiwan
Yist Y. Lin Taiwan
Da-Rong Liu Taiwan
Kyu J. Han United States
Ganesh Sivaraman United States
Yi-Jian Wu China
Preethi Jyothi India
Songxiang Liu Hong Kong
Ravichander Vipperla France
Jian-Lai Zhou China
Po-Han Chi relative to Andy T. Liu Taiwan Andy T. Liu's profile →
Citations per field
00.5×1.5×
Andy T. Liu · 1×
Citations per year

Countries citing papers authored by Po-Han Chi

Since Specialization
Citations

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

Fields of papers citing papers by Po-Han Chi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Po-Han Chi. 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 Po-Han Chi. The network helps show where Po-Han Chi may publish in the future.

Co-authors

The 19 scholars most cited alongside Po-Han Chi, 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 Po-Han Chi Line = papers co-authored together Po-Han Chi links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1
SUPERB: Speech Processing Universal PERformance Benchmark
Hit paper breakdown →
2021409
2 2021117
3
Further Boosting BERT-based Models by Duplicating Existing Layers: Some Intriguing Phenomena inside BERT
20201

About Po-Han Chi

Po-Han Chi is a scholar working on Artificial Intelligence, Signal Processing, Infectious Diseases, Organic Chemistry and Surgery, having authored 3 papers that have together received 527 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Speech Recognition and Synthesis (2 papers), Machine Learning and Data Classification (1 paper) and Music and Audio Processing (1 paper). The work is most often cited by research in Signal Processing (293 citations), Artificial Intelligence (439 citations), Experimental and Cognitive Psychology (69 citations), Computer Vision and Pattern Recognition (42 citations) and Developmental Biology (4 citations). Po-Han Chi has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Hung-yi Lee, Shang-Wen Li, Da-Rong Liu, Shinji Watanabe, Wei-Cheng Tseng, Kushal Lakhotia, Yist Y. Lin, Guan-Ting Lin, Shu-Wen Yang and Zili Huang. Their work appears in journals such as arXiv (Cornell University).

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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