Slava Shechtman
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Speech and dialogue systems
- Natural Language Processing Techniques
- Topic Modeling
Papers in
-
- Speech Recognition and Synthesis 28
- Speech and dialogue systems 8
- Natural Language Processing Techniques 8
- Topic Modeling 3
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- Speech and Audio Processing 19
- Music and Audio Processing 8
- Co-authors
- A. S. Sorin (10 shared papers)D. Malah (4 shared papers)Zvi Kons (6 shared papers)Ron Hoory (8 shared papers)R. Bakis (2 shared papers)Raul Castro Fernandez (6 shared papers)Yong Qin (1 shared paper)David Haws (4 shared papers)
- Journals
- IEEE Transactions on Audio Speech and Language Processing (3 papers)SSW (1 paper)Interspeech 2022 (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIsraelAustria
In The Last Decade
Slava Shechtman
28 papers receiving 158 citations
Peers
Comparison fields: 5 of 23
- Signal Processing 141
- Artificial Intelligence 180
- Experimental and Cognitive Psychology 26
- Computer Vision and Pattern Recognition 20
- Human-Computer Interaction 4
Countries citing papers authored by Slava Shechtman
This map shows the geographic impact of Slava Shechtman'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 Slava Shechtman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Slava Shechtman more than expected).
Fields of papers citing papers by Slava Shechtman
This network shows the impact of papers produced by Slava Shechtman. 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 Slava Shechtman. The network helps show where Slava Shechtman may publish in the future.
Co-authors
The 24 scholars most cited alongside Slava Shechtman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 33 | |
| 2 | 2006 | 20 | |
| 3 | 2006 | 16 | |
| 4 | 2011 | 14 | |
| 5 | 2005 | 14 | |
| 6 | 2010 | 12 | |
| 7 | 2020 | 11 | |
| 8 | 2017 | 8 | |
| 9 | 2021 | 8 | |
| 10 | 2010 | 8 | |
| 11 | 2018 | 7 | |
| 12 | 2018 | 6 | |
| 13 | 2021 | 6 | |
| 14 | 2018 | 5 | |
| 15 | 2011 | 4 | |
| 16 | 2010 | 4 | |
| 17 | 2006 | 3 | |
| 18 | 2008 | 3 | |
| 19 | 2022 | 3 | |
| 20 | 2023 | 2 |
About Slava Shechtman
Slava Shechtman is a scholar working on Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Pharmacy, having authored 29 papers that have together received 199 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (28 papers), Speech and Audio Processing (19 papers), Speech and dialogue systems (8 papers), Natural Language Processing Techniques (8 papers), Music and Audio Processing (8 papers), Phonetics and Phonology Research (4 papers), Topic Modeling (3 papers) and Advanced Data Compression Techniques (3 papers). The work is most often cited by research in Signal Processing (141 citations), Artificial Intelligence (180 citations), Experimental and Cognitive Psychology (26 citations), Computer Vision and Pattern Recognition (20 citations) and Human-Computer Interaction (4 citations). Slava Shechtman has collaborated with scholars based in United States, Israel and Austria. Frequent co-authors include A. S. Sorin, D. Malah, Zvi Kons, Ron Hoory, R. Bakis, Raul Castro Fernandez, Yong Qin, David Haws, Daniel Chazan and Yosi Mass. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, SSW, Interspeech 2022 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.