RJ Skerry-Ryan

3.9k total citations
8 papers, 429 citations indexed

About

RJ Skerry-Ryan is a scholar working on Artificial Intelligence, Signal Processing and Cancer Research. According to data from OpenAlex, RJ Skerry-Ryan has authored 8 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Signal Processing and 1 paper in Cancer Research. Recurrent topics in RJ Skerry-Ryan's work include Speech Recognition and Synthesis (7 papers), Natural Language Processing Techniques (5 papers) and Speech and dialogue systems (4 papers). RJ Skerry-Ryan is often cited by papers focused on Speech Recognition and Synthesis (7 papers), Natural Language Processing Techniques (5 papers) and Speech and dialogue systems (4 papers). RJ Skerry-Ryan collaborates with scholars based in United States and China. RJ Skerry-Ryan's co-authors include Yuxuan Wang, Daisy Stanton, Yu Zhang, Yonghui Wu, Jia Ye, Ron J. Weiss, Heiga Zen, Rif A. Saurous, Ying Xiao and Wei-Ning Hsu and has published in prestigious journals such as arXiv (Cornell University), International Conference on Machine Learning and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

In The Last Decade

RJ Skerry-Ryan

8 papers receiving 378 citations

Peers

RJ Skerry-Ryan

AI

SP

CVPR

ECP

CSE

Tanel Alumäe Estonia

Ramya Rasipuram Switzerland

Laurent Besacier France

Rob Clark United States

V.R.R. Gadde United States

Yatharth Saraf United States

G. Evermann United Kingdom

Zhehuai Chen United States

Jacob Kahn Israel

Yusuke Ijima Japan

Tanel Alumäe Estonia

RJ Skerry-Ryan

427 ×1.1

AI

118 ×0.5

SP

46 ×1.2

CVPR

19 ×0.8

ECP

6 ×0.7

CSE

Citations per year, relative to RJ Skerry-Ryan RJ Skerry-Ryan (= 1×) peers Tanel Alumäe

Countries citing papers authored by RJ Skerry-Ryan

Since Specialization

Citations

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

Fields of papers citing papers by RJ Skerry-Ryan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by RJ Skerry-Ryan. 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 RJ Skerry-Ryan. The network helps show where RJ Skerry-Ryan may publish in the future.

Co-authorship network of co-authors of RJ Skerry-Ryan

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

All Works

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8 of 8 papers shown

1.

Stanton, Daisy, Matt Shannon, Soroosh Mariooryad, et al.. (2022). Speaker Generation. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7897–7901. 11 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.

Zhang, Yu, Ron J. Weiss, Heiga Zen, et al.. (2019). Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning. 2080–2084. 97 indexed citations

4.

Chung, Yu-An, Yuxuan Wang, Wei-Ning Hsu, Yu Zhang, & RJ Skerry-Ryan. (2019). Semi-supervised Training for Improving Data Efficiency in End-to-end Speech Synthesis. 6940–6944. 57 indexed citations

5.

Wang, Yuxuan, Daisy Stanton, Yu Zhang, et al.. (2018). Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis. International Conference on Machine Learning. 5180–5189. 62 indexed citations

6.

Shafran, Izhak, Tom Bagby, & RJ Skerry-Ryan. (2018). Complex Evolution Recurrent Neural Networks (ceRNNs). 5854–5858. 6 indexed citations

7.

Stanton, Daisy, Yuxuan Wang, & RJ Skerry-Ryan. (2018). Predicting Expressive Speaking Style from Text in End-To-End Speech Synthesis. 595–602. 73 indexed citations

8.

Wang, Yuxuan, RJ Skerry-Ryan, Daisy Stanton, et al.. (2017). Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model.. arXiv (Cornell University). 86 indexed citations

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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