Zvi Kons
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Speech and dialogue systems
- Topic Modeling
Papers in
-
- Speech Recognition and Synthesis 14
- Speech and dialogue systems 4
- Natural Language Processing Techniques 3
- Topic Modeling 2
-
- Speech and Audio Processing 7
- Music and Audio Processing 5
- Co-authors
- Orith Toledo‐Ronen (1 shared paper)Ron Hoory (9 shared papers)Slava Shechtman (6 shared papers)Hagai Aronowitz (2 shared papers)D. Malah (1 shared paper)Michael Picheny (2 shared papers)Hong-Kwang Jeff Kuo (2 shared papers)Samuel Thomas (2 shared papers)
- Journals
- Applied Soft Computing (1 paper)IEEE Transactions on Audio Speech and Language Processing (1 paper)Interspeech 2022 (1 paper)KTH Publication Database DiVA (KTH Royal Institute of Technology) (1 paper)
- Partner nations
- United StatesIsraelLithuania
In The Last Decade
Zvi Kons
14 papers receiving 166 citations
Peers
Comparison fields: 5 of 33
- Signal Processing 124
- Artificial Intelligence 149
- Developmental Biology 4
- Experimental and Cognitive Psychology 13
- Computer Vision and Pattern Recognition 21
Countries citing papers authored by Zvi Kons
This map shows the geographic impact of Zvi Kons'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 Zvi Kons with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zvi Kons more than expected).
Fields of papers citing papers by Zvi Kons
This network shows the impact of papers produced by Zvi Kons. 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 Zvi Kons. The network helps show where Zvi Kons may publish in the future.
Co-authors
The 25 scholars most cited alongside Zvi Kons, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 36 | |
| 2 | 2020 | 35 | |
| 3 | 2010 | 33 | |
| 4 | 2013 | 21 | |
| 5 | 2014 | 16 | |
| 6 | 2005 | 14 | |
| 7 | 2002 | 10 | |
| 8 | 2018 | 7 | |
| 9 | 2006 | 3 | |
| 10 | 2008 | 3 | |
| 11 | 2014 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2017 | 2 |
About Zvi Kons
Zvi Kons is a scholar working on Artificial Intelligence, Signal Processing, Physiology, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 14 papers that have together received 186 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (14 papers), Speech and Audio Processing (7 papers), Music and Audio Processing (5 papers), Speech and dialogue systems (4 papers), Natural Language Processing Techniques (3 papers), Topic Modeling (2 papers), Voice and Speech Disorders (2 papers) and Advanced Data Compression Techniques (1 paper). The work is most often cited by research in Signal Processing (124 citations), Artificial Intelligence (149 citations), Developmental Biology (4 citations), Experimental and Cognitive Psychology (13 citations) and Computer Vision and Pattern Recognition (21 citations). Zvi Kons has collaborated with scholars based in United States, Israel and Lithuania. Frequent co-authors include Orith Toledo‐Ronen, Ron Hoory, Slava Shechtman, Hagai Aronowitz, D. Malah, Michael Picheny, Hong-Kwang Jeff Kuo, Samuel Thomas, A. S. Sorin and Kartik Audhkhasi. Their work appears in journals such as Applied Soft Computing, IEEE Transactions on Audio Speech and Language Processing, Interspeech 2022 and KTH Publication Database DiVA (KTH Royal Institute of Technology).
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.