Yatharth Saraf
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition
- Experimental and Cognitive Psychology
- Physiology
- Co-authors
- Kritika SinghAndros TjandraAlexis ConneauMichael AuliAlexei BaevskiQiantong XuNaman GoyalJuan Pino
- Topics
- Speech Recognition and Synthesis (13 papers)Natural Language Processing Techniques (8 papers)Music and Audio Processing (7 papers)
- Journals
- International Journal of Computer MathematicsICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Interspeech 2022
- Partner nations
- United StatesIndiaIsrael
In The Last Decade
Yatharth Saraf
16 papers receiving 425 citations
Hit Papers
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 385
- Signal Processing 225
- Computer Vision and Pattern Recognition 57
- Experimental and Cognitive Psychology 23
- Physiology 13
Countries citing papers authored by Yatharth Saraf
This map shows the geographic impact of Yatharth Saraf'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 Yatharth Saraf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yatharth Saraf more than expected).
Fields of papers citing papers by Yatharth Saraf
This network shows the impact of papers produced by Yatharth Saraf. 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 Yatharth Saraf. The network helps show where Yatharth Saraf may publish in the future.
Co-authorship network of co-authors of Yatharth Saraf
This figure shows the co-authorship network connecting the top 25 collaborators of Yatharth Saraf. A scholar is included among the top collaborators of Yatharth Saraf 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 Yatharth Saraf. Yatharth Saraf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scalebreakdown → | 266 |
| 3 | 25 | |
| 4 | 5 | |
| 5 | 5 | |
| 6 | 44 | |
| 7 | 14 | |
| 8 | 18 | |
| 9 | 7 | |
| 10 | 28 | |
| 11 | Multilingual Graphemic Hybrid ASR with Massive Data Augmentation. | 5 |
| 12 | 8 | |
| 13 | 1 | |
| 14 | 17 | |
| 15 | Multilingual ASR with Massive Data Augmentation. | 0 |
| 16 | Algorithms for Image Segmentation | 3 |
| 17 | 3 |
About Yatharth Saraf
Yatharth Saraf is a scholar working on Signal Processing, Artificial Intelligence and Computer Science Applications, having authored 17 papers that have together received 459 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (13 papers), Natural Language Processing Techniques (8 papers) and Music and Audio Processing (7 papers). The work is most often cited by research in Signal Processing (225 citations), Artificial Intelligence (385 citations) and Computer Vision and Pattern Recognition (57 citations). Yatharth Saraf has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Kritika Singh, Andros Tjandra, Alexis Conneau, Michael Auli, Alexei Baevski, Qiantong Xu, Naman Goyal, Juan Pino, Patrick von Platen and Changhan Wang. Their work appears in journals such as International Journal of Computer Mathematics, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 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.