Dominik Roblek
- Signal Processing top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Computer Networks and Communications
- Co-authors
- Marco TagliasacchiKevin KilgourMatt SharifiOlivier PietquinNeil ZeghidourOlivier TeboulDavid GrangierRaphaël Marinier
- Topics
- Music and Audio Processing (7 papers)Speech and Audio Processing (6 papers)Speech Recognition and Synthesis (5 papers)
- Journals
- IEEE Signal Processing LettersIEEE/ACM Transactions on Audio Speech and Language ProcessingArrow@dit (Dublin Institute of Technology)
- Partner nations
- United StatesSwitzerlandIreland
In The Last Decade
Dominik Roblek
9 papers receiving 372 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Signal Processing 239
- Artificial Intelligence 221
- Computer Vision and Pattern Recognition 122
- Cognitive Neuroscience 33
- Computer Networks and Communications 24
Countries citing papers authored by Dominik Roblek
This map shows the geographic impact of Dominik Roblek'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 Dominik Roblek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dominik Roblek more than expected).
Fields of papers citing papers by Dominik Roblek
This network shows the impact of papers produced by Dominik Roblek. 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 Dominik Roblek. The network helps show where Dominik Roblek may publish in the future.
Co-authorship network of co-authors of Dominik Roblek
This figure shows the co-authorship network connecting the top 25 collaborators of Dominik Roblek. A scholar is included among the top collaborators of Dominik Roblek 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 Dominik Roblek. Dominik Roblek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | AudioLM: A Language Modeling Approach to Audio Generationbreakdown → | 201 |
| 2 | 32 | |
| 3 | 4 | |
| 4 | 30 | |
| 5 | 28 | |
| 6 | 0 | |
| 7 | 81 | |
| 8 | 5 | |
| 9 | 15 | |
| 10 | Decentralized Discovery and Execution for Composite Semantic Web Services | 3 |
About Dominik Roblek
Dominik Roblek is a scholar working on Signal Processing, Artificial Intelligence and Information Systems, having authored 10 papers that have together received 399 indexed citations. Recurring topics across this work include Music and Audio Processing (7 papers), Speech and Audio Processing (6 papers) and Speech Recognition and Synthesis (5 papers). The work is most often cited by research in Signal Processing (239 citations), Artificial Intelligence (221 citations) and Computer Vision and Pattern Recognition (122 citations). Dominik Roblek has collaborated with scholars based in United States, Switzerland and Ireland. Frequent co-authors include Marco Tagliasacchi, Kevin Kilgour, Matt Sharifi, Olivier Pietquin, Neil Zeghidour, Olivier Teboul, David Grangier, Raphaël Marinier, Eugene Kharitonov and Damien Vincent. Their work appears in journals such as IEEE Signal Processing Letters, IEEE/ACM Transactions on Audio Speech and Language Processing and Arrow@dit (Dublin Institute of Technology).
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.