Harriet J. Nock
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Cognitive Neuroscience
- Co-authors
- Giridharan IyengarC. NetiSanjeev KhudanpurMurat SaraçlarMilind NaphadeJohn R. SmithChing‐Yung LinSteve Young
- Topics
- Music and Audio Processing (17 papers)Speech and Audio Processing (13 papers)Speech Recognition and Synthesis (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaCommunications of the ACMCognitive Science
- Partner nations
- United StatesUnited KingdomTürkiye
In The Last Decade
Harriet J. Nock
32 papers receiving 549 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 371
- Signal Processing 304
- Computer Vision and Pattern Recognition 282
- Experimental and Cognitive Psychology 96
- Cognitive Neuroscience 19
Countries citing papers authored by Harriet J. Nock
This map shows the geographic impact of Harriet J. Nock'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 Harriet J. Nock with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harriet J. Nock more than expected).
Fields of papers citing papers by Harriet J. Nock
This network shows the impact of papers produced by Harriet J. Nock. 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 Harriet J. Nock. The network helps show where Harriet J. Nock may publish in the future.
Co-authorship network of co-authors of Harriet J. Nock
This figure shows the co-authorship network connecting the top 25 collaborators of Harriet J. Nock. A scholar is included among the top collaborators of Harriet J. Nock 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 Harriet J. Nock. Harriet J. Nock is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | ICT Tools for Searching, Annotation and Analysis of Audiovisual Media | 1 |
| 3 | 8 | |
| 4 | 2 | |
| 5 | 18 | |
| 6 | 4 | |
| 7 | 6 | |
| 8 | 13 | |
| 9 | 42 | |
| 10 | 15 | |
| 11 | 5 | |
| 12 | 4 | |
| 13 | IBM Research TREC 2002 Video Retrieval System. | 36 |
| 14 | 4 | |
| 15 | 13 | |
| 16 | Techniques for modelling Phonological Processes in Automatic Speech Recognition | 9 |
| 17 | 81 | |
| 18 | 18 | |
| 19 | Detecting and correcting poor pronunciations for multiword units | 9 |
| 20 | 20 |
About Harriet J. Nock
Harriet J. Nock is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 32 papers that have together received 646 indexed citations. Recurring topics across this work include Music and Audio Processing (17 papers), Speech and Audio Processing (13 papers) and Speech Recognition and Synthesis (13 papers). The work is most often cited by research in Signal Processing (304 citations), Computer Vision and Pattern Recognition (282 citations) and Artificial Intelligence (371 citations). Harriet J. Nock has collaborated with scholars based in United States, United Kingdom and Türkiye. Frequent co-authors include Giridharan Iyengar, C. Neti, Sanjeev Khudanpur, Murat Saraçlar, Milind Naphade, John R. Smith, Ching‐Yung Lin, Steve Young, Chuck Wooters and Bill Byrne. Their work appears in journals such as SHILAP Revista de lepidopterología, Communications of the ACM and Cognitive Science.
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.