Mervyn Jack

80 papers receiving 1.8k citations

Peers

Mervyn Jack
Comparison fields: 5 of 113
  • Signal Processing 654
  • Human-Computer Interaction 259
  • Artificial Intelligence 919
  • Computer Vision and Pattern Recognition 310
  • Information Systems 339
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Alexander I. Rudnicky United States
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Citations per year

Countries citing papers authored by Mervyn Jack

Since Specialization
Citations

This map shows the geographic impact of Mervyn Jack'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 Mervyn Jack with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mervyn Jack more than expected).

Fields of papers citing papers by Mervyn Jack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mervyn Jack. 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 Mervyn Jack. The network helps show where Mervyn Jack may publish in the future.

Co-authors

The 25 scholars most cited alongside Mervyn Jack, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mervyn Jack Line = papers co-authored together Mervyn Jack links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Hidden Markov Models for Speech Recognition
1991489
2
Proceedings of International Conference on Acoustics Speech and Signal Processing ICASSP’98
1998291
3 1993126
4 2010122
5 200893
6
Proceedings of EUROSPEECH-97
199773
7 200967
8 200560
9
Proceedings 6th European Conference on Speech Communication and Technology (Eurospeech 99)
199955
10 200244
11 200643
12 201030
13 201228
14 199327
15 198323
16 200023
17 200820
18 201020
19
Proceedings of HCI 2004
200418
20 200617

About Mervyn Jack

Mervyn Jack is a scholar working on Artificial Intelligence, Human-Computer Interaction, Signal Processing, Information Systems and Experimental and Cognitive Psychology, having authored 87 papers that have together received 2.0k indexed citations. Recurring topics across this work include Speech and dialogue systems (17 papers), Speech Recognition and Synthesis (16 papers), Speech and Audio Processing (9 papers), Phonetics and Phonology Research (8 papers), Technology Adoption and User Behaviour (7 papers), User Authentication and Security Systems (6 papers), Usability and User Interface Design (6 papers) and Wikis in Education and Collaboration (5 papers). The work is most often cited by research in Signal Processing (654 citations), Human-Computer Interaction (259 citations), Artificial Intelligence (919 citations), Computer Vision and Pattern Recognition (310 citations) and Information Systems (339 citations). Mervyn Jack has collaborated with scholars based in United Kingdom, Brazil and United States. Frequent co-authors include Xuedong Huang, Yasuo Ariki, Hazel Morton, Fergus McInnes, Steven Hiller, Gary Douglas, James Anderson, Benjamin R. Cowan, Mark S. Schmidt and John Laver. Their work appears in journals such as Interacting with Computers, Computer Assisted Language Learning, The Journal of the Acoustical Society of America, Speech Communication and Computers & Security.

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.

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