David Harwath
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Cognitive Neuroscience
- Experimental and Cognitive Psychology
- Co-authors
- James GlassAntonio TorralbaTimothy J. HazenGalen ChuangDídac SurísAdrià RecasensSamuel ThomasRogério Feris
- Topics
- Speech Recognition and Synthesis (21 papers)Multimodal Machine Learning Applications (15 papers)Speech and Audio Processing (14 papers)
- Journals
- International Journal of Computer VisionIEEE/ACM Transactions on Audio Speech and Language Processing2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United StatesTaiwanGermany
In The Last Decade
David Harwath
43 papers receiving 503 citations
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 325
- Computer Vision and Pattern Recognition 277
- Signal Processing 231
- Cognitive Neuroscience 20
- Experimental and Cognitive Psychology 20
Countries citing papers authored by David Harwath
This map shows the geographic impact of David Harwath'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 David Harwath with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Harwath more than expected).
Fields of papers citing papers by David Harwath
This network shows the impact of papers produced by David Harwath. 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 David Harwath. The network helps show where David Harwath may publish in the future.
Co-authorship network of co-authors of David Harwath
This figure shows the co-authorship network connecting the top 25 collaborators of David Harwath. A scholar is included among the top collaborators of David Harwath 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 David Harwath. David Harwath is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 12 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 21 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 16 | |
| 14 | 53 | |
| 15 | 25 | |
| 16 | 46 | |
| 17 | Grounding Spoken Words in Unlabeled Video | 9 |
| 18 | Unsupervised learning of spoken language with visual context | 112 |
| 19 | 8 | |
| 20 | 1 |
About David Harwath
David Harwath is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 542 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (21 papers), Multimodal Machine Learning Applications (15 papers) and Speech and Audio Processing (14 papers). The work is most often cited by research in Signal Processing (231 citations), Computer Vision and Pattern Recognition (277 citations) and Artificial Intelligence (325 citations). David Harwath has collaborated with scholars based in United States, Taiwan and Germany. Frequent co-authors include James Glass, Antonio Torralba, Timothy J. Hazen, Galen Chuang, Dídac Surís, Adrià Recasens, Samuel Thomas, Rogério Feris, Shinji Watanabe and Changan Chen. Their work appears in journals such as International Journal of Computer Vision, IEEE/ACM Transactions on Audio Speech and Language Processing and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.