Yogesh Virkar

520 total citations
15 papers, 266 citations indexed

About

Yogesh Virkar is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yogesh Virkar has authored 15 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 5 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yogesh Virkar's work include Natural Language Processing Techniques (9 papers), Speech Recognition and Synthesis (6 papers) and Music and Audio Processing (4 papers). Yogesh Virkar is often cited by papers focused on Natural Language Processing Techniques (9 papers), Speech Recognition and Synthesis (6 papers) and Music and Audio Processing (4 papers). Yogesh Virkar collaborates with scholars based in United States and Germany. Yogesh Virkar's co-authors include Aaron Clauset, Marcello Federico, Roberto Barra-Chicote, Prashant Mathur, Juan G. Restrepo, Edward Ott, Woodrow L. Shew, Brian J. Thompson, William Brannon and James D. Meiss and has published in prestigious journals such as Physical review. E, Transactions of the Association for Computational Linguistics and The Annals of Applied Statistics.

In The Last Decade

Yogesh Virkar

14 papers receiving 254 citations

Peers

Yogesh Virkar

AI

SNP

CVPR

SP

LL

John Stonham United Kingdom

Khalid Daoudi France

Didier A. Vega‐Oliveros Brazil

C. A. Young United States

George Datseris Germany

Jamie Smith United States

Sucharita Ghosh Switzerland

K. Hauke Kraemer Germany

Changgui Gu China

Oriol Pont France

John Stonham United Kingdom

Yogesh Virkar

133 ×2.1

AI

36 ×0.7

SNP

47 ×1.2

CVPR

12 ×0.3

SP

112 ×3.2

LL

Citations per year, relative to Yogesh Virkar Yogesh Virkar (= 1×) peers John Stonham

Countries citing papers authored by Yogesh Virkar

Since Specialization

Citations

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

Fields of papers citing papers by Yogesh Virkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yogesh Virkar

This figure shows the co-authorship network connecting the top 25 collaborators of Yogesh Virkar. A scholar is included among the top collaborators of Yogesh Virkar 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 Yogesh Virkar. Yogesh Virkar 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:

15 of 15 papers shown

1.

Kang, Woo Hyun, et al.. (2024). SWAN: SubWord Alignment Network for HMM-free word timing estimation in end-to-end automatic speech recognition. 2910–2914.

2.

Thompson, Brian J., et al.. (2023). Improving Isochronous Machine Translation with Target Factors and Auxiliary Counters. 37–41. 2 indexed citations

3.

Brannon, William, Yogesh Virkar, & Brian J. Thompson. (2023). Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing. Transactions of the Association for Computational Linguistics. 11. 419–435. 7 indexed citations

4.

Virkar, Yogesh, et al.. (2022). Prosodic alignment for off-screen automatic dubbing. Interspeech 2022. 496–500. 6 indexed citations

5.

Tam, Derek, et al.. (2022). Isochrony-Aware Neural Machine Translation for Automatic Dubbing. Interspeech 2022. 1776–1780. 7 indexed citations

6.

Virkar, Yogesh, et al.. (2022). ISOMETRIC MT: Neural Machine Translation for Automatic Dubbing. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 6242–6246. 13 indexed citations

7.

Virkar, Yogesh, et al.. (2022). Duration Modeling of Neural TTS for Automatic Dubbing. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8037–8041. 6 indexed citations

8.

Federico, Marcello, et al.. (2021). Machine Translation Verbosity Control for Automatic Dubbing. 7538–7542. 10 indexed citations

9.

Virkar, Yogesh, et al.. (2021). Improvements to Prosodic Alignment for Automatic Dubbing. 7543–7574. 12 indexed citations

10.

Sharma, Mayank, et al.. (2021). Intra-Sentential Speaking Rate Control in Neural Text-To-Speech for Automatic Dubbing. 3151–3155. 2 indexed citations

11.

Virkar, Yogesh, Juan G. Restrepo, Woodrow L. Shew, & Edward Ott. (2020). Dynamic regulation of resource transport induces criticality in interdependent networks of excitable units. Physical review. E. 101(2). 22303–22303. 2 indexed citations

12.

Federico, Marcello, et al.. (2020). Evaluating and Optimizing Prosodic Alignment for Automatic Dubbing. 1481–1485. 17 indexed citations

13.

Virkar, Yogesh, Woodrow L. Shew, Juan G. Restrepo, & Edward Ott. (2016). Feedback control stabilization of critical dynamics via resource transport on multilayer networks: How glia enable learning dynamics in the brain. Physical review. E. 94(4). 12 indexed citations

14.

Virkar, Yogesh, Juan G. Restrepo, & James D. Meiss. (2015). Hamiltonian mean field model: Effect of network structure on synchronization dynamics. Physical Review E. 92(5). 52802–52802. 5 indexed citations

15.

Virkar, Yogesh & Aaron Clauset. (2014). Power-law distributions in binned empirical data. The Annals of Applied Statistics. 8(1). 165 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.

Explore authors with similar magnitude of impact