Jonathan Shen
Impact in
- Signal Processing top 0.5%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 1%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
Papers in ⓘ
-
- Speech Recognition and Synthesis 7
- Natural Language Processing Techniques 4
- Topic Modeling 2
- Speech and dialogue systems 2
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- Speech and Audio Processing 2
- Music and Audio Processing 2
- Co-authors
- Yonghui Wu (5 shared papers)Ron J. Weiss (3 shared papers)Ruoming Pang (2 shared papers)Zhifeng Chen (2 shared papers)Yu Zhang (1 shared paper)Rif A. Saurous (1 shared paper)Mike Schuster (1 shared paper)Zongheng Yang (1 shared paper)
- Journals
- Neural Information Processing Systems (1 paper)Interspeech 2022 (1 paper)
- Partner nations
- United States
In The Last Decade
Jonathan Shen
7 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Signal Processing 936
- Artificial Intelligence 1.4k
- Computer Vision and Pattern Recognition 205
- Experimental and Cognitive Psychology 90
- Developmental Biology 7
Countries citing papers authored by Jonathan Shen
This map shows the geographic impact of Jonathan Shen'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 Jonathan Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Shen more than expected).
Fields of papers citing papers by Jonathan Shen
This network shows the impact of papers produced by Jonathan Shen. 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 Jonathan Shen. The network helps show where Jonathan Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan Shen, 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 | Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions Hit paper breakdown → | 2018 | 1414 |
| 2 | Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis | 2018 | 90 |
| 3 | 2021 | 50 | |
| 4 | 2021 | 42 | |
| 5 | 2021 | 37 | |
| 6 | 2022 | 4 | |
| 7 | 2020 | 1 |
About Jonathan Shen
Jonathan Shen is a scholar working on Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology, Infectious Diseases and Organic Chemistry, having authored 7 papers that have together received 1.6k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (7 papers), Natural Language Processing Techniques (4 papers), Speech and Audio Processing (2 papers), Music and Audio Processing (2 papers), Topic Modeling (2 papers), Speech and dialogue systems (2 papers) and Phonetics and Phonology Research (1 paper). The work is most often cited by research in Signal Processing (936 citations), Artificial Intelligence (1.4k citations), Computer Vision and Pattern Recognition (205 citations), Experimental and Cognitive Psychology (90 citations) and Developmental Biology (7 citations). Jonathan Shen has collaborated with scholars based in United States. Frequent co-authors include Yonghui Wu, Ron J. Weiss, Ruoming Pang, Zhifeng Chen, Yu Zhang, Rif A. Saurous, Mike Schuster, Zongheng Yang, Yuxuan Wang and Navdeep Jaitly. Their work appears in journals such as Neural Information Processing Systems and Interspeech 2022.
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.