Lasse Borgholt
Impact in
- Signal Processing top 10%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
- Machine Learning in Healthcare
Papers in
-
- Topic Modeling 3
- Speech Recognition and Synthesis 3
- Machine Learning in Healthcare 2
- Sentiment Analysis and Opinion Mining 1
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- Music and Audio Processing 3
- Co-authors
- Jakob D. Havtorn (6 shared papers)Lars Maaløe (6 shared papers)Joakim Edin (4 shared papers)Christian Igel (3 shared papers)Hung-yi Lee (2 shared papers)Abdelrahman Mohamed (2 shared papers)Katrin Kirchhoff (2 shared papers)Shang-Wen Li (2 shared papers)
- Journals
- npj Digital Medicine (1 paper)IEEE Journal of Selected Topics in Signal Processing (1 paper)arXiv (Cornell University) (3 papers)Research at the University of Copenhagen (University of Copenhagen) (2 papers)
- Partner nations
- DenmarkUnited StatesTaiwan
In The Last Decade
Lasse Borgholt
7 papers receiving 245 citations
Lasse Borgholt's Hit Papers
Peers
Comparison fields: 5 of 48
- Signal Processing 97
- Artificial Intelligence 187
- Health Informatics 4
- Health Information Management 8
- Experimental and Cognitive Psychology 21
Countries citing papers authored by Lasse Borgholt
This map shows the geographic impact of Lasse Borgholt'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 Lasse Borgholt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lasse Borgholt more than expected).
Fields of papers citing papers by Lasse Borgholt
This network shows the impact of papers produced by Lasse Borgholt. 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 Lasse Borgholt. The network helps show where Lasse Borgholt may publish in the future.
Co-authors
The 22 scholars most cited alongside Lasse Borgholt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Self-Supervised Speech Representation Learning: A Review Hit paper breakdown → | 2022 | 214 |
| 2 | 2023 | 19 | |
| 3 | 2023 | 8 | |
| 4 | 2015 | 5 | |
| 5 | 2020 | 4 | |
| 6 | 2022 | 2 | |
| 7 | 2024 | 1 |
About Lasse Borgholt
Lasse Borgholt is a scholar working on Artificial Intelligence, Signal Processing, Molecular Biology, Pulmonary and Respiratory Medicine and Cognitive Neuroscience, having authored 7 papers that have together received 253 indexed citations. Recurring topics across this work include Music and Audio Processing (3 papers), Topic Modeling (3 papers), Speech Recognition and Synthesis (3 papers), Biomedical Text Mining and Ontologies (2 papers), Machine Learning in Healthcare (2 papers), Stock Market Forecasting Methods (1 paper), Sentiment Analysis and Opinion Mining (1 paper) and EEG and Brain-Computer Interfaces (1 paper). The work is most often cited by research in Signal Processing (97 citations), Artificial Intelligence (187 citations), Health Informatics (4 citations), Health Information Management (8 citations) and Experimental and Cognitive Psychology (21 citations). Lasse Borgholt has collaborated with scholars based in Denmark, United States and Taiwan. Frequent co-authors include Jakob D. Havtorn, Lars Maaløe, Joakim Edin, Christian Igel, Hung-yi Lee, Abdelrahman Mohamed, Katrin Kirchhoff, Shang-Wen Li, Karen Livescu and Shinji Watanabe. Their work appears in journals such as npj Digital Medicine, IEEE Journal of Selected Topics in Signal Processing, arXiv (Cornell University) and Research at the University of Copenhagen (University of Copenhagen).
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.