Martin Krawczyk

451 citations
9 papers · 334 indexed · h-index 7
Topics
Speech and Audio Processing (9 papers)Advanced Adaptive Filtering Techniques (7 papers)Blind Source Separation Techniques (3 papers)
Journals
IEEE Signal Processing LettersIEEE/ACM Transactions on Audio Speech and Language ProcessingProceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing
Partner nations
Germany

In The Last Decade

Martin Krawczyk

8 papers receiving 323 citations

Peers

Martin Krawczyk
Comparison fields: 5 of 33
  • Signal Processing 317
  • Computational Mechanics 238
  • Artificial Intelligence 77
  • Cognitive Neuroscience 72
  • Computer Vision and Pattern Recognition 26
Replace F. Jabloun with:
F. Jabloun Canada
Benjamin J. Shannon Australia
Éric Plourde Canada
Ivo Merks United States
Martin Krawczyk-Becker Germany
Colin Breithaupt Germany
Zhaozhang Jin United States
Jan Mark de Haan Denmark
Wouter Tirry Belgium
Volker Leutnant Germany
Martin Krawczyk relative to F. Jabloun Canada F. Jabloun's profile →
Citations per field
00.5×5.8×
F. Jabloun · 1×
Citations per year

Countries citing papers authored by Martin Krawczyk

Since Specialization
Citations

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

Fields of papers citing papers by Martin Krawczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Krawczyk

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Krawczyk. A scholar is included among the top collaborators of Martin Krawczyk based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Krawczyk. Martin Krawczyk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 150
2 0
3
Phase-sensitive real-time capable speech enhancement under voiced-unvoiced uncertainty
10
4
STFT Phase Improvement for Single Channel Speech Enhancement
27
5 12
6 55
7 6
8 17
9 57

About Martin Krawczyk

Martin Krawczyk is a scholar working on Signal Processing, Computational Mechanics and Cognitive Neuroscience, having authored 9 papers that have together received 334 indexed citations. Recurring topics across this work include Speech and Audio Processing (9 papers), Advanced Adaptive Filtering Techniques (7 papers) and Blind Source Separation Techniques (3 papers). The work is most often cited by research in Signal Processing (317 citations), Computational Mechanics (238 citations) and Cognitive Neuroscience (72 citations). Martin Krawczyk has collaborated with scholars based in Germany. Frequent co-authors include Timo Gerkmann, Rainer Martin, Colin Breithaupt, Gerald Enzner and M. Weinert. Their work appears in journals such as IEEE Signal Processing Letters, IEEE/ACM Transactions on Audio Speech and Language Processing and Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal 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.

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