S. Levinson

5.0k citations
86 papers · 3.2k indexed · 1 hit paper · h-index 22

S. Levinson

77 papers receiving 2.8k citations

Hit Papers

An Introduction to the Application of the Theory of Proba...6711983202619972011200400600

Peers

S. Levinson
Comparison fields: 5 of 142
  • Signal Processing 1.8k
  • Artificial Intelligence 2.3k
  • Computer Vision and Pattern Recognition 767
  • Experimental and Cognitive Psychology 215
  • Human-Computer Interaction 58
Replace B.-H. Juang with:
B.-H. Juang United States
H. Bourlard Switzerland
Bhuvana Ramabhadran United States
Joe Frankel United Kingdom
Frank K. Soong China
H. Gish United States
Roberto Togneri Australia
Nelson Morgan United States
William M. Campbell United States
Yasuo Ariki Japan
S. Levinson relative to B.-H. Juang United States B.-H. Juang's profile →
Citations per field
00.5×1.7×
B.-H. Juang · 1×
Citations per year

Countries citing papers authored by S. Levinson

Since Specialization
Citations

This map shows the geographic impact of S. Levinson'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 S. Levinson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Levinson more than expected).

Fields of papers citing papers by S. Levinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Levinson. 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 S. Levinson. The network helps show where S. Levinson may publish in the future.

Co-authorship network

The 25 scholars most cited alongside S. Levinson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S. Levinson Line = papers co-authored together S. Levinson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20087
3 20064
4 20051
5 20055
6 20053
7 20058
8 20034
9 20028
10 20011
11
Adaptive acquisition of language
19922
12 199133
13 199147
14 1986160
15 198560
16 198317
17 19831
18 197960
19 1978268
20 197819

About S. Levinson

S. Levinson is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Radiation, having authored 86 papers that have together received 3.2k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (47 papers), Speech and Audio Processing (31 papers), Speech and dialogue systems (24 papers), Music and Audio Processing (20 papers), Natural Language Processing Techniques (14 papers), Time Series Analysis and Forecasting (12 papers), Bayesian Methods and Mixture Models (7 papers) and Advanced Data Compression Techniques (7 papers). The work is most often cited by research in Signal Processing (1.8k citations), Artificial Intelligence (2.3k citations), Computer Vision and Pattern Recognition (767 citations), Experimental and Cognitive Psychology (215 citations) and Human-Computer Interaction (58 citations). S. Levinson has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include L. R. Rabiner, M. M. Sondhi, A. E. Rosenberg, B.-H. Juang, J. Wilpon, Andrej Ljolje, Thomas S. Huang, Allen L. Gorin, Brian Pianfetti and Dan Roth. Their work appears in journals such as The Journal of the Acoustical Society of America, Computer Speech & Language, IEEE Communications Magazine, IEEE Transactions on Signal Processing and Proceedings of the National Academy of Sciences.

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.

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