Jacob Kahn
Impact in
- Signal Processing top 2%
- Music and Audio Processing
- Speech and Audio Processing
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Music and Audio Processing 8
- Speech and Audio Processing 5
-
- Speech Recognition and Synthesis 10
- Natural Language Processing Techniques 3
- Topic Modeling 2
- Co-authors
- Awni Hannun (5 shared papers)Gabriel Synnaeve (7 shared papers)Ronan Collobert (7 shared papers)Ann Lee (3 shared papers)Vitaliy Liptchinsky (3 shared papers)Qiantong Xu (6 shared papers)Emmanuel Dupoux (1 shared paper)Wenlong Zheng (1 shared paper)
- Journals
- arXiv (Cornell University) (7 papers)
- Partner nations
- IsraelUnited StatesFrance
In The Last Decade
Jacob Kahn
10 papers receiving 644 citations
Jacob Kahn's Hit Papers
Peers
Comparison fields: 5 of 46
- Signal Processing 366
- Artificial Intelligence 608
- Computer Vision and Pattern Recognition 62
- Experimental and Cognitive Psychology 32
- Human-Computer Interaction 5
Countries citing papers authored by Jacob Kahn
This map shows the geographic impact of Jacob Kahn'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 Jacob Kahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob Kahn more than expected).
Fields of papers citing papers by Jacob Kahn
This network shows the impact of papers produced by Jacob Kahn. 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 Jacob Kahn. The network helps show where Jacob Kahn may publish in the future.
Co-authors
The 25 scholars most cited alongside Jacob Kahn, 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 | Libri-Light: A Benchmark for ASR with Limited or No Supervision Hit paper breakdown → | 2020 | 326 |
| 2 | 2020 | 132 | |
| 3 | 2019 | 103 | |
| 4 | 2020 | 79 | |
| 5 | 2023 | 17 | |
| 6 | 2021 | 11 | |
| 7 | 2020 | 7 | |
| 8 | 2021 | 5 | |
| 9 | 2021 | 4 | |
| 10 | Self-Training for End-to-End Speech Recognition - ICASSP 2020 Slides | 2020 | 1 |
About Jacob Kahn
Jacob Kahn is a scholar working on Signal Processing, Artificial Intelligence, Insect Science, Renewable Energy, Sustainability and the Environment and Obstetrics and Gynecology, having authored 10 papers that have together received 685 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (10 papers), Music and Audio Processing (8 papers), Speech and Audio Processing (5 papers), Natural Language Processing Techniques (3 papers) and Topic Modeling (2 papers). The work is most often cited by research in Signal Processing (366 citations), Artificial Intelligence (608 citations), Computer Vision and Pattern Recognition (62 citations), Experimental and Cognitive Psychology (32 citations) and Human-Computer Interaction (5 citations). Jacob Kahn has collaborated with scholars based in Israel, United States and France. Frequent co-authors include Awni Hannun, Gabriel Synnaeve, Ronan Collobert, Ann Lee, Vitaliy Liptchinsky, Qiantong Xu, Emmanuel Dupoux, Wenlong Zheng, Eugene Kharitonov and Pierre-Emmanuel Mazaré. Their work appears in journals such as arXiv (Cornell University).
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.