Daniel Leech‐Wilkinson

1.5k citations
45 papers · 300 · h-index 10

Impact in

  • Music top 0.5%
    • Musicology and Musical Analysis
    • Diverse Music Education Insights
    • Music History and Culture
    • Diverse Musicological Studies
    • Neuroscience and Music Perception

Papers in

    • Musicology and Musical Analysis 20
    • Diverse Musicological Studies 7
    • Diverse Music Education Insights 6
    • Neuroscience and Music Perception 11

Daniel Leech‐Wilkinson

33 papers receiving 235 citations

Peers

Daniel Leech‐Wilkinson
Comparison fields: 5 of 44
  • Music 157
  • Cognitive Neuroscience 133
  • Classics 20
  • Signal Processing 54
  • Experimental and Cognitive Psychology 59
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Citations per year

Countries citing papers authored by Daniel Leech‐Wilkinson

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Leech‐Wilkinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Leech‐Wilkinson. 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 Daniel Leech‐Wilkinson. The network helps show where Daniel Leech‐Wilkinson may publish in the future.

Co-authors

The 6 scholars most cited alongside Daniel Leech‐Wilkinson, 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 Daniel Leech‐Wilkinson Line = papers co-authored together Daniel Leech‐Wilkinson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201440
2 200934
3 201333
4 201622
5 201220
6 200618
7 198412
8 198411
9 201010
10 201810
11
Challenging Performance: Classical Music Performance Norms and How to Escape Them
20208
12 20177
13 20077
14 19826
15
Machaut's Music: New Interpretations.
20036
16 20106
17
Le livre dou voir dit : The book of the true poem
19985
18 20155
19 19954
20 20063

About Daniel Leech‐Wilkinson

Daniel Leech‐Wilkinson is a scholar working on Music, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Signal Processing and History and Philosophy of Science, having authored 45 papers that have together received 300 indexed citations. Recurring topics across this work include Musicology and Musical Analysis (20 papers), Neuroscience and Music Perception (11 papers), Music Technology and Sound Studies (10 papers), Music and Audio Processing (10 papers), Diverse Musicological Studies (7 papers), Diverse Music Education Insights (6 papers), Medieval European Literature and History (4 papers) and Historical Studies and Socio-cultural Analysis (4 papers). The work is most often cited by research in Music (157 citations), Cognitive Neuroscience (133 citations), Classics (20 citations), Signal Processing (54 citations) and Experimental and Cognitive Psychology (59 citations). Daniel Leech‐Wilkinson has collaborated with scholars based in United States, United Kingdom and Brazil. Frequent co-authors include Mats B. Küssner, Dan Tidhar, R. Barton Palmer, Nicholas Cook, Sarah Fuller and Nicolas Gold. Their work appears in journals such as Musicae Scientiae, Early Music, Music Analysis, Frontiers in Psychology and Psychology of Music.

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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