Miloš Cerňak
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Experimental and Cognitive Psychology top 10%
- Physiology
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Philip N. GarnerPetr MotlíčekAfsaneh AsaeiHervé BourlardJuan Rafael Orozco‐ArroyaveElmar NöthJuan Camilo Vásquez-CorreaHeidi Christensen
- Topics
- Speech Recognition and Synthesis (48 papers)Speech and Audio Processing (40 papers)Music and Audio Processing (23 papers)
- Journals
- IEEE Signal Processing MagazineFrontiers in Human NeuroscienceIEEE Signal Processing Letters
- Partner nations
- SwitzerlandSlovakiaUnited Kingdom
In The Last Decade
Miloš Cerňak
54 papers receiving 429 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 365
- Signal Processing 282
- Experimental and Cognitive Psychology 125
- Physiology 85
- Computer Vision and Pattern Recognition 63
Countries citing papers authored by Miloš Cerňak
This map shows the geographic impact of Miloš Cerňak'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 Miloš Cerňak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miloš Cerňak more than expected).
Fields of papers citing papers by Miloš Cerňak
This network shows the impact of papers produced by Miloš Cerňak. 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 Miloš Cerňak. The network helps show where Miloš Cerňak may publish in the future.
Co-authorship network of co-authors of Miloš Cerňak
This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Cerňak. A scholar is included among the top collaborators of Miloš Cerňak 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 Miloš Cerňak. Miloš Cerňak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 8 | |
| 7 | 22 | |
| 8 | 4 | |
| 9 | 16 | |
| 10 | 40 | |
| 11 | Cognitive Speech Coding | 1 |
| 12 | 20 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 7 | |
| 16 | 13 | |
| 17 | 1 | |
| 18 | A Comparison of Decision Tree Classifiers for Automatic Diagnosis of Speech Recognition Errors. | 10 |
| 19 | Baseline System for Automatic Speech Recognition with French GlobalPhone Database | 0 |
| 20 | Diagnostics of speech recognition using classification phoneme diagnostic trees | 2 |
About Miloš Cerňak
Miloš Cerňak is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 61 papers that have together received 487 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (48 papers), Speech and Audio Processing (40 papers) and Music and Audio Processing (23 papers). The work is most often cited by research in Signal Processing (282 citations), Artificial Intelligence (365 citations) and Experimental and Cognitive Psychology (125 citations). Miloš Cerňak has collaborated with scholars based in Switzerland, Slovakia and United Kingdom. Frequent co-authors include Philip N. Garner, Petr Motlíček, Afsaneh Asaei, Hervé Bourlard, Juan Rafael Orozco‐Arroyave, Elmar Nöth, Juan Camilo Vásquez-Correa, Heidi Christensen, Alexandre Hyafil and Frank Rudzicz. Their work appears in journals such as IEEE Signal Processing Magazine, Frontiers in Human Neuroscience and IEEE Signal Processing Letters.
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.