Dominik Roblek

827 total citations · 1 hit paper
10 papers, 399 citations indexed

About

Dominik Roblek is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Dominik Roblek has authored 10 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Signal Processing and 3 papers in Computer Networks and Communications. Recurrent topics in Dominik Roblek's work include Music and Audio Processing (7 papers), Speech and Audio Processing (6 papers) and Speech Recognition and Synthesis (5 papers). Dominik Roblek is often cited by papers focused on Music and Audio Processing (7 papers), Speech and Audio Processing (6 papers) and Speech Recognition and Synthesis (5 papers). Dominik Roblek collaborates with scholars based in United States, Switzerland and Ireland. Dominik Roblek's co-authors include Marco Tagliasacchi, Kevin Kilgour, Matt Sharifi, Olivier Pietquin, Neil Zeghidour, Olivier Teboul, David Grangier, Raphaël Marinier, Eugene Kharitonov and Damien Vincent and has published in prestigious journals such as IEEE Signal Processing Letters, IEEE/ACM Transactions on Audio Speech and Language Processing and Arrow@dit (Dublin Institute of Technology).

In The Last Decade

Dominik Roblek

9 papers receiving 372 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

AudioLM: A Language Modeling Approach to Audio Generation

2023 201 citations Zalán Borsos, Raphaël Marinier et al. IEEE/ACM Transactions on Audio Speech and Language Processing profile →

Peers

Dominik Roblek

SP

AI

CVPR

CN

CNC

Chai Wutiwiwatchai Thailand

Andrew Morris Switzerland

Thomas Kemp Germany

Damien Vincent France

Willie Walker United Kingdom

Mouldi Bedda Algeria

F. Alleva United States

Giridharan Iyengar United States

Neil Zeghidour United States

Qiantong Xu Israel

Chai Wutiwiwatchai Thailand

Dominik Roblek

246 ×1.0

SP

360 ×1.6

AI

113 ×0.9

CVPR

18 ×0.5

CN

45 ×1.9

CNC

Citations per year, relative to Dominik Roblek Dominik Roblek (= 1×) peers Chai Wutiwiwatchai

Countries citing papers authored by Dominik Roblek

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Borsos, Zalán, Raphaël Marinier, Damien Vincent, et al.. (2023). AudioLM: A Language Modeling Approach to Audio Generation. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 2523–2533. 201 indexed citations breakdown →

2.

Li, Yunpeng, et al.. (2021). Real-Time Speech Frequency Bandwidth Extension. 691–695. 32 indexed citations

3.

Gfeller, Beat, et al.. (2020). Pitch Estimation Via Self-Supervision. 17. 3527–3531. 4 indexed citations

4.

Lin, James, et al.. (2020). Training Keyword Spotters with Limited and Synthesized Speech Data. 7474–7478. 30 indexed citations

5.

Tagliasacchi, Marco, Beat Gfeller, Félix de Chaumont Quitry, & Dominik Roblek. (2020). Pre-Training Audio Representations With Self-Supervision. IEEE Signal Processing Letters. 27. 600–604. 28 indexed citations

6.

Tagliasacchi, Marco, Félix de Chaumont Quitry, & Dominik Roblek. (2020). Multi-Task Adapters for On-Device Audio Inference. IEEE Signal Processing Letters. 27. 630–634.

7.

Kilgour, Kevin, et al.. (2019). Fréchet Audio Distance: A Reference-Free Metric for Evaluating Music Enhancement Algorithms. 2350–2354. 81 indexed citations

8.

Keeney, John, et al.. (2008). Knowledge-based semantic clustering. 460–467. 5 indexed citations

9.

Keeney, John, et al.. (2008). Extending Siena to support more expressive and flexible subscriptions. Arrow@dit (Dublin Institute of Technology). 5403. 35–46. 15 indexed citations

10.

Roblek, Dominik. (2006). Decentralized Discovery and Execution for Composite Semantic Web Services. 3 indexed citations

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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