Rohit Prabhavalkar
- Artificial Intelligence top 0.5%
- Signal Processing top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Co-authors
- Tara N. SainathKanishka RaoHaşim SakRaziel ÁlvarezBo LiAnjuli KannanGolan PundakYanzhang He
- Topics
- Speech Recognition and Synthesis (52 papers)Speech and Audio Processing (33 papers)Music and Audio Processing (26 papers)
- Journals
- Proceedings of the IEEEIEEE/ACM Transactions on Audio Speech and Language ProcessingarXiv (Cornell University)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Rohit Prabhavalkar
56 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 1.6k
- Signal Processing 1.0k
- Computer Vision and Pattern Recognition 154
- Electrical and Electronic Engineering 47
- Control and Systems Engineering 38
Countries citing papers authored by Rohit Prabhavalkar
This map shows the geographic impact of Rohit Prabhavalkar'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 Rohit Prabhavalkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rohit Prabhavalkar more than expected).
Fields of papers citing papers by Rohit Prabhavalkar
This network shows the impact of papers produced by Rohit Prabhavalkar. 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 Rohit Prabhavalkar. The network helps show where Rohit Prabhavalkar may publish in the future.
Co-authorship network of co-authors of Rohit Prabhavalkar
This figure shows the co-authorship network connecting the top 25 collaborators of Rohit Prabhavalkar. A scholar is included among the top collaborators of Rohit Prabhavalkar 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 Rohit Prabhavalkar. Rohit Prabhavalkar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 16 | |
| 7 | 76 | |
| 8 | 14 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | Model Unit Exploration for Sequence-to-Sequence Speech Recognition. | 5 |
| 13 | 50 | |
| 14 | 95 | |
| 15 | 28 | |
| 16 | 178 | |
| 17 | 193 | |
| 18 | 97 | |
| 19 | 26 | |
| 20 | Investigations into the Crandem Approach to Word Recognition | 2 |
About Rohit Prabhavalkar
Rohit Prabhavalkar is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 59 papers that have together received 1.8k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (52 papers), Speech and Audio Processing (33 papers) and Music and Audio Processing (26 papers). The work is most often cited by research in Signal Processing (1.0k citations), Artificial Intelligence (1.6k citations) and Computer Vision and Pattern Recognition (154 citations). Rohit Prabhavalkar has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Tara N. Sainath, Kanishka Rao, Haşim Sak, Raziel Álvarez, Bo Li, Anjuli Kannan, Golan Pundak, Yanzhang He, Ruoming Pang and Ian McGraw. Their work appears in journals such as Proceedings of the IEEE, IEEE/ACM Transactions on Audio Speech and Language Processing and 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.