Jon Barker

6.7k citations
131 papers · 3.4k · 1 hit paper · h-index 25

Impact in

Papers in

Jon Barker

126 papers receiving 3.0k citations

Jon Barker's Hit Papers

An audio-visual corpus for speech perception and automatic speech recognition 2006 · 761 citations
7610+6+13Years since publication250500750

Peers

Jon Barker
Comparison fields: 5 of 93
  • Signal Processing 2.8k
  • Artificial Intelligence 1.6k
  • Cognitive Neuroscience 742
  • Experimental and Cognitive Psychology 330
  • Computational Mechanics 537
Replace John G. Beerends with:
John G. Beerends Netherlands
Takuya Yoshioka Japan
H. J. M. Steeneken Netherlands
Mike Brookes United Kingdom
Tomohiro Nakatani Japan
Dirk Van Compernolle Belgium
Masashi Unoki Japan
Ivan Tashev United States
Toshio Irino Japan
Masato Akagi Japan
Jon Barker relative to John G. Beerends Netherlands John G. Beerends's profile →
Citations per field
00.5×3.4×
John G. Beerends · 1×
Citations per year

Countries citing papers authored by Jon Barker

Since Specialization
Citations

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

Fields of papers citing papers by Jon Barker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jon Barker, 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 Jon Barker Line = papers co-authored together Jon Barker links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An audio-visual corpus for speech perception and automatic speech recognition
Hit paper breakdown →
2006761
2 2016235
3 2013196
4 2008182
5 2012155
6 200496
7 200095
8 200189
9 201087
10 201673
11 200671
12 201859
13 201959
14 202050
15 200447
16 201547
17 202145
18 200545
19 201344
20 200739

About Jon Barker

Jon Barker is a scholar working on Signal Processing, Artificial Intelligence, Cognitive Neuroscience, Computational Mechanics and Experimental and Cognitive Psychology, having authored 131 papers that have together received 3.4k indexed citations. Recurring topics across this work include Speech and Audio Processing (106 papers), Speech Recognition and Synthesis (70 papers), Music and Audio Processing (51 papers), Hearing Loss and Rehabilitation (34 papers), Blind Source Separation Techniques (14 papers), Advanced Adaptive Filtering Techniques (9 papers), Voice and Speech Disorders (9 papers) and Noise Effects and Management (8 papers). The work is most often cited by research in Signal Processing (2.8k citations), Artificial Intelligence (1.6k citations), Cognitive Neuroscience (742 citations), Experimental and Cognitive Psychology (330 citations) and Computational Mechanics (537 citations). Jon Barker has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Martin Cooke, Xu Shao, Stuart Cunningham, Emmanuel Vincent, Heidi Christensen, Phil Green, Ning Ma, Shinji Watanabe, Ricard Marxer and María Luisa García Lecumberri. Their work appears in journals such as Speech Communication, The Journal of the Acoustical Society of America, Computer Speech & Language, IEEE Transactions on Audio Speech and Language Processing and Data in Brief.

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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