G. Zavaliagkos
- Signal Processing top 2%
- Speech and Audio Processing 16
- Music and Audio Processing 7
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis 27
- Natural Language Processing Techniques 12
- Neural Networks and Applications 9
- Speech and dialogue systems 4
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- Advanced Data Compression Techniques 5
- Handwritten Text Recognition Techniques 2
- Co-authors
- Richard SchwartzJ. MakhoulYing ZhaoJ. McDonoughS. AustinChuck WootersBill ByrneMichael Finke
- Journals
- IEEE Transactions on Speech and Audio Processing (1 paper)Speech Communication (2 papers)International Journal of Pattern Recognition and Artificial Intelligence (1 paper)
- Partner nations
- United StatesUnited KingdomMexico
In The Last Decade
G. Zavaliagkos
29 papers receiving 391 citations
Peers
Comparison fields: 5 of 36
- Signal Processing 322
- Artificial Intelligence 459
- Experimental and Cognitive Psychology 54
- Computer Vision and Pattern Recognition 51
- Human-Computer Interaction 6
Countries citing papers authored by G. Zavaliagkos
This map shows the geographic impact of G. Zavaliagkos'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 G. Zavaliagkos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Zavaliagkos more than expected).
Fields of papers citing papers by G. Zavaliagkos
This network shows the impact of papers produced by G. Zavaliagkos. 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 G. Zavaliagkos. The network helps show where G. Zavaliagkos may publish in the future.
Co-authorship network
The 25 scholars most cited alongside G. Zavaliagkos, 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 | 2002 | 12 | |
| 2 | 2002 | 46 | |
| 3 | 2002 | 3 | |
| 4 | 2002 | 4 | |
| 5 | 2002 | 7 | |
| 6 | 2002 | 1 | |
| 7 | 2002 | 13 | |
| 8 | 2000 | 6 | |
| 9 | 1998 | 6 | |
| 10 | 1995 | 21 | |
| 11 | 1994 | 7 | |
| 12 | 1994 | 50 | |
| 13 | 1994 | 11 | |
| 14 | Segmental Neural Net Optimization for Continuous Speech Recognition | 1993 | 1 |
| 15 | 1993 | 8 | |
| 16 | A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition | 1992 | 3 |
| 17 | 1992 | 23 | |
| 18 | 1992 | 33 | |
| 19 | 1992 | 3 | |
| 20 | 1991 | 12 |
About G. Zavaliagkos
G. Zavaliagkos is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 487 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (27 papers), Speech and Audio Processing (16 papers), Natural Language Processing Techniques (12 papers), Neural Networks and Applications (9 papers), Music and Audio Processing (7 papers), Advanced Data Compression Techniques (5 papers), Speech and dialogue systems (4 papers) and Handwritten Text Recognition Techniques (2 papers). The work is most often cited by research in Signal Processing (322 citations), Artificial Intelligence (459 citations) and Experimental and Cognitive Psychology (54 citations). G. Zavaliagkos has collaborated with scholars based in United States, United Kingdom and Mexico. Frequent co-authors include Richard Schwartz, J. Makhoul, Ying Zhao, J. McDonough, S. Austin, Chuck Wooters, Bill Byrne, Michael Finke, Harriet J. Nock and John McDonough. Their work appears in journals such as IEEE Transactions on Speech and Audio Processing, Speech Communication and International Journal of Pattern Recognition and Artificial Intelligence.
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.