David Vandyke
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Social Psychology
- Signal Processing
- Co-authors
- Nikola MrkšićPei-Hao SuTsung-Hsien WenMilica GašićSteve YoungStefan UltesLina M. Rojas BarahonaYixuan Su
- Topics
- Topic Modeling (14 papers)Speech and dialogue systems (12 papers)Natural Language Processing Techniques (8 papers)
- Journals
- Computer Speech & LanguageApollo (University of Cambridge)ANU Open Research (Australian National University)
- Partner nations
- United KingdomAustraliaUnited States
In The Last Decade
David Vandyke
19 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 240
- Information Systems 81
- Social Psychology 31
- Signal Processing 29
Countries citing papers authored by David Vandyke
This map shows the geographic impact of David Vandyke'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 Vandyke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Vandyke more than expected).
Fields of papers citing papers by David Vandyke
This network shows the impact of papers produced by David Vandyke. 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 Vandyke. The network helps show where David Vandyke may publish in the future.
Co-authorship network of co-authors of David Vandyke
This figure shows the co-authorship network connecting the top 25 collaborators of David Vandyke. A scholar is included among the top collaborators of David Vandyke 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 Vandyke. David Vandyke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 43 | |
| 2 | 10 | |
| 3 | 7 | |
| 4 | 13 | |
| 5 | 75 | |
| 6 | A Network-based End-to-End Trainable Task-oriented Dialogue Systembreakdown → | 451 |
| 7 | 64 | |
| 8 | 18 | |
| 9 | 12 | |
| 10 | 37 | |
| 11 | Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systemsbreakdown → | 466 |
| 12 | 13 | |
| 13 | 14 | |
| 14 | 19 | |
| 15 | 24 | |
| 16 | 1 | |
| 17 | 4 | |
| 18 | 1 | |
| 19 | Speaker Identification Using Glottal-Source Waveforms and Support-Vector-Machine Modelling | 6 |
About David Vandyke
David Vandyke is a scholar working on Artificial Intelligence, Signal Processing and Pharmacy, having authored 19 papers that have together received 1.3k indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Speech and dialogue systems (12 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (240 citations) and Information Systems (81 citations). David Vandyke has collaborated with scholars based in United Kingdom, Australia and United States. Frequent co-authors include Nikola Mrkšić, Pei-Hao Su, Tsung-Hsien Wen, Milica Gašić, Steve Young, Stefan Ultes, Lina M. Rojas Barahona, Yixuan Su, Nigel Collier and Sihui Wang. Their work appears in journals such as Computer Speech & Language, Apollo (University of Cambridge) and ANU Open Research (Australian National 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.