M. Krasner
Impact in
- Signal Processing top 10%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Speech and dialogue systems
- Algorithms and Data Compression
- Neural Networks and Applications
Papers in
-
- Speech Recognition and Synthesis 10
- Algorithms and Data Compression 3
- Speech and dialogue systems 2
-
- Speech and Audio Processing 10
- Music and Audio Processing 2
- Co-authors
- Richard Schwartz (9 shared papers)S. Roucos (8 shared papers)J. Makhoul (6 shared papers)Y.-L. Chow (4 shared papers)Owen Kimball (5 shared papers)H. Gish (3 shared papers)Jared J. Wolf (4 shared papers)M. Dunham (3 shared papers)
- Journals
- The Journal of the Acoustical Society of America (2 papers)Proceedings of the International Conference on Parallel Processing (1 paper)
- Partner nations
- United States
In The Last Decade
M. Krasner
11 papers receiving 90 citations
Peers
Comparison fields: 5 of 29
- Signal Processing 78
- Artificial Intelligence 104
- Computer Vision and Pattern Recognition 39
- Experimental and Cognitive Psychology 6
- Hardware and Architecture 3
Countries citing papers authored by M. Krasner
This map shows the geographic impact of M. Krasner'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 M. Krasner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Krasner more than expected).
Fields of papers citing papers by M. Krasner
This network shows the impact of papers produced by M. Krasner. 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 M. Krasner. The network helps show where M. Krasner may publish in the future.
Co-authors
The 15 scholars most cited alongside M. Krasner, 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 | 2005 | 31 | |
| 2 | 2005 | 26 | |
| 3 | 2005 | 18 | |
| 4 | 2005 | 12 | |
| 5 | 1988 | 8 | |
| 6 | 2005 | 8 | |
| 7 | 2005 | 7 | |
| 8 | 2005 | 7 | |
| 9 | 1982 | 5 | |
| 10 | 2005 | 3 | |
| 11 | 2005 | 2 | |
| 12 | Continuous Speech Recognition on a Butterfly Parallel Processor. | 1986 | 1 |
| 13 | 1979 | 1 | |
| 14 | 2005 | 1 | |
| 15 | 2005 | 0 | |
| 16 | 2005 | 0 |
About M. Krasner
M. Krasner is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics and Civil and Structural Engineering, having authored 16 papers that have together received 130 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (10 papers), Speech and Audio Processing (10 papers), Advanced Data Compression Techniques (7 papers), Algorithms and Data Compression (3 papers), Music and Audio Processing (2 papers), Speech and dialogue systems (2 papers), Advanced Adaptive Filtering Techniques (2 papers) and Structural Health Monitoring Techniques (1 paper). The work is most often cited by research in Signal Processing (78 citations), Artificial Intelligence (104 citations), Computer Vision and Pattern Recognition (39 citations), Experimental and Cognitive Psychology (6 citations) and Hardware and Architecture (3 citations). M. Krasner has collaborated with scholars based in United States. Frequent co-authors include Richard Schwartz, S. Roucos, J. Makhoul, Y.-L. Chow, Owen Kimball, H. Gish, Jared J. Wolf, M. Dunham, P. Price and Francis Kubala. Their work appears in journals such as The Journal of the Acoustical Society of America and Proceedings of the International Conference on Parallel Processing.
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.