Jonathan Shen

4.0k total citations · 1 hit paper
7 papers, 1.6k citations indexed

About

Jonathan Shen is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Jonathan Shen has authored 7 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Signal Processing and 1 paper in Experimental and Cognitive Psychology. Recurrent topics in Jonathan Shen's work include Speech Recognition and Synthesis (7 papers), Natural Language Processing Techniques (4 papers) and Speech and dialogue systems (2 papers). Jonathan Shen is often cited by papers focused on Speech Recognition and Synthesis (7 papers), Natural Language Processing Techniques (4 papers) and Speech and dialogue systems (2 papers). Jonathan Shen collaborates with scholars based in United States. Jonathan Shen's co-authors include Yonghui Wu, Ron J. Weiss, Ruoming Pang, Zhifeng Chen, Rif A. Saurous, Yuxuan Wang, Navdeep Jaitly, Yu Zhang, Zongheng Yang and Mike Schuster and has published in prestigious journals such as Neural Information Processing Systems and Interspeech 2022.

In The Last Decade

Jonathan Shen

7 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions

2018 1.4k citations Jonathan Shen, Ruoming Pang et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jonathan Shen United States	5	1.4k	936	205	90	45	7	1.6k
Zhengyang Chen China	14	1.1k 0.8×	892 1.0×	145 0.7×	137 1.5×	39 0.9×	50	1.4k
Sanyuan Chen China	13	1.1k 0.8×	763 0.8×	126 0.6×	136 1.5×	31 0.7×	26	1.4k
Rohit Sinha India	19	946 0.7×	900 1.0×	130 0.6×	112 1.2×	61 1.4×	123	1.2k
Berrak Şişman Singapore	19	926 0.7×	726 0.8×	150 0.7×	150 1.7×	65 1.4×	59	1.2k
Keiichiro Oura Japan	15	920 0.7×	666 0.7×	101 0.5×	107 1.2×	19 0.4×	69	1.1k
Shinnosuke Takamichi Japan	16	756 0.5×	682 0.7×	115 0.6×	64 0.7×	33 0.7×	116	978
Seiichi Nakagawa Japan	21	1.3k 1.0×	1.0k 1.1×	187 0.9×	159 1.8×	30 0.7×	257	1.6k
Mitchell McLaren United States	24	1.7k 1.2×	1.6k 1.7×	184 0.9×	94 1.0×	30 0.7×	84	1.9k
Eduardo Lleida Spain	18	984 0.7×	850 0.9×	159 0.8×	142 1.6×	139 3.1×	145	1.3k
Pegah Ghahremani United States	12	1.1k 0.8×	901 1.0×	65 0.3×	136 1.5×	42 0.9×	18	1.3k

Countries citing papers authored by Jonathan Shen

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Jonathan Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Shen. A scholar is included among the top collaborators of Jonathan Shen 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 Jonathan Shen. Jonathan Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Zen, Heiga, Norman Casagrande, Chun-an Chan, et al.. (2022). Training Text-To-Speech Systems From Synthetic Data: A Practical Approach For Accent Transfer Tasks. Interspeech 2022. 4571–4575. 4 indexed citations

2.

Elias, Isaac, Heiga Zen, Jonathan Shen, et al.. (2021). Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling. 141–145. 37 indexed citations

3.

Ye, Jia, Heiga Zen, Jonathan Shen, Yu Zhang, & Yonghui Wu. (2021). PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTS. 151–155. 42 indexed citations

4.

Elias, Isaac, Heiga Zen, Jonathan Shen, et al.. (2021). Parallel Tacotron: Non-Autoregressive and Controllable TTS. 5709–5713. 50 indexed citations

5.

Wan, Vincent, et al.. (2020). Modelling Intonation in Spectrograms for Neural Vocoder based Text-to-Speech. 945–949. 1 indexed citations

6.

Ye, Jia, Yu Zhang, Ron J. Weiss, et al.. (2018). Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis. Neural Information Processing Systems. 31. 4480–4490. 90 indexed citations

7.

Shen, Jonathan, Ruoming Pang, Ron J. Weiss, et al.. (2018). Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions. 4779–4783. 1414 indexed citations breakdown →

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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