Simon Dixon

6.5k citations
166 papers · 3.7k · h-index 31

Impact in

Papers in

Simon Dixon

162 papers receiving 3.3k citations

Peers

Simon Dixon
Comparison fields: 5 of 115
  • Signal Processing 3.2k
  • Computer Vision and Pattern Recognition 2.7k
  • Music 334
  • Cognitive Neuroscience 1.0k
  • Developmental Biology 44
Replace Yi‐Hsuan Yang with:
Yi‐Hsuan Yang Taiwan
Xavier Serra Spain
Perfecto Herrera Spain
Fabien Gouyon Portugal
George Tzanetakis Canada
François Pachet Japan
Douglas Eck Canada
Ichiro Fujinaga Canada
Lie Lu China
Patrick Cook United States
Simon Dixon relative to Yi‐Hsuan Yang Taiwan Yi‐Hsuan Yang's profile →
Citations per field
00.5×1.5×1.8×
Yi‐Hsuan Yang · 1×
Citations per year

Countries citing papers authored by Simon Dixon

Since Specialization
Citations

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

Fields of papers citing papers by Simon Dixon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 166 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001229
2 2014223
3 2013176
4 2016149
5 2006138
6 2018137
7 2007105
8
A Survey of Music Recommendation Systems and Future Perspectives
201299
9 200591
10 201086
11 200984
12 200480
13 200580
14
Evaluating Rhythmic descriptors for Musical Genre Classification
200478
15 200476
16 201472
17 201565
18 201756
19 200354
20 201254

About Simon Dixon

Simon Dixon is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Music, having authored 166 papers that have together received 3.7k indexed citations. Recurring topics across this work include Music and Audio Processing (154 papers), Music Technology and Sound Studies (129 papers), Speech and Audio Processing (72 papers), Neuroscience and Music Perception (54 papers), Diverse Musicological Studies (9 papers), Time Series Analysis and Forecasting (8 papers), Speech Recognition and Synthesis (7 papers) and Natural Language Processing Techniques (4 papers). The work is most often cited by research in Signal Processing (3.2k citations), Computer Vision and Pattern Recognition (2.7k citations), Music (334 citations), Cognitive Neuroscience (1.0k citations) and Developmental Biology (44 citations). Simon Dixon has collaborated with scholars based in United Kingdom, Austria and United States. Frequent co-authors include Matthias Mauch, Emmanouil Benetos, Gerhard Widmer, Fabien Gouyon, Siddharth Sigtia, Elias Pampalk, Anssi Klapuri, Marcus T. Pearce, Holger Kirchhoff and Sebastian Ewert. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE/ACM Transactions on Audio Speech and Language Processing, Journal of New Music Research, Computer Music Journal and Music Perception An Interdisciplinary Journal.

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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