Frank Rudzicz
- Artificial Intelligence top 0.5%
- Physiology top 2%
- Cognitive Neuroscience top 2%
- Signal Processing top 1%
- Experimental and Cognitive Psychology top 2%
- Co-authors
- Kathleen FraserJed A. MeltzerAravind Kumar NamasivayamJudy Hanwen ShenMaria YanchevaShunan ZhaoJames ShawTrevor Jamieson
- Topics
- Speech Recognition and Synthesis (43 papers)Topic Modeling (39 papers)Natural Language Processing Techniques (32 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Frank Rudzicz
174 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Artificial Intelligence 1.8k
- Physiology 817
- Cognitive Neuroscience 704
- Signal Processing 680
- Experimental and Cognitive Psychology 586
Countries citing papers authored by Frank Rudzicz
This map shows the geographic impact of Frank Rudzicz'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 Frank Rudzicz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Rudzicz more than expected).
Fields of papers citing papers by Frank Rudzicz
This network shows the impact of papers produced by Frank Rudzicz. 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 Frank Rudzicz. The network helps show where Frank Rudzicz may publish in the future.
Co-authorship network of co-authors of Frank Rudzicz
This figure shows the co-authorship network connecting the top 25 collaborators of Frank Rudzicz. A scholar is included among the top collaborators of Frank Rudzicz 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 Frank Rudzicz. Frank Rudzicz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 5 | |
| 3 | 14 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 10 | |
| 7 | 2 | |
| 8 | 21 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 11 | |
| 12 | 7 | |
| 13 | 37 | |
| 14 | 11 | |
| 15 | 38 | |
| 16 | 25 | |
| 17 | Communication strategies for a computerized caregiver for individuals with Alzheimer’s disease | 4 |
| 18 | Using acoustic measures to predict automatic speech recognition performance for dysarthric speakers. | 5 |
| 19 | T-RES: TEST OF RATING OF EMOTIONS IN SPEECH: INTERACTION OF AFFECTIVE CUES EXPRESSED IN LEXICAL CONTENT AND PROSODY OF SPOKEN SENTENCES | 1 |
| 20 | Towards a noisy-channel model of dysarthria in speech recognition | 4 |
About Frank Rudzicz
Frank Rudzicz is a scholar working on Artificial Intelligence, Signal Processing and Health Informatics, having authored 182 papers that have together received 3.8k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (43 papers), Topic Modeling (39 papers) and Natural Language Processing Techniques (32 papers). The work is most often cited by research in Health Informatics (265 citations), Signal Processing (680 citations) and Artificial Intelligence (1.8k citations). Frank Rudzicz has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Kathleen Fraser, Jed A. Meltzer, Aravind Kumar Namasivayam, Judy Hanwen Shen, Maria Yancheva, Shunan Zhao, James Shaw, Trevor Jamieson, Avi Goldfarb and Teodor Grantcharov. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.