Brian McFee

62 papers receiving 3.6k citations

Brian McFee's Hit Papers

librosa: Audio and Music Signal Analysis in Python 2015 · 1.9k citations
1.9k0+3+7Years since publication50010001.5k

Peers

Brian McFee
Comparison fields: 5 of 136
  • Signal Processing 2.6k
  • Developmental Biology 208
  • Computer Vision and Pattern Recognition 1.8k
  • Music 161
  • Artificial Intelligence 1.1k
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Colin Raffel United States
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Jort F. Gemmeke Belgium
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Countries citing papers authored by Brian McFee

Since Specialization
Citations

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

Fields of papers citing papers by Brian McFee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1
librosa: Audio and Music Signal Analysis in Python
Hit paper breakdown →
20151897
2
Metric Learning to Rank
2010207
3 2014204
4 2012115
5 2018102
6 201293
7 201087
8 201786
9 201569
10
Robust Structural Metric Learning
201368
11 201063
12 201162
13 201859
14 201557
15 201250
16 201743
17 201440
18 200932
19 201432
20 201831

About Brian McFee

Brian McFee is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience and Music, having authored 63 papers that have together received 3.9k indexed citations. Recurring topics across this work include Music and Audio Processing (44 papers), Music Technology and Sound Studies (27 papers), Speech and Audio Processing (16 papers), Diverse Musicological Studies (7 papers), Neuroscience and Music Perception (7 papers), Speech Recognition and Synthesis (7 papers), Advanced Image and Video Retrieval Techniques (7 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Signal Processing (2.6k citations), Developmental Biology (208 citations), Computer Vision and Pattern Recognition (1.8k citations), Music (161 citations) and Artificial Intelligence (1.1k citations). Brian McFee has collaborated with scholars based in United States, Austria and France. Frequent co-authors include Gert Lanckriet, Daniel P. W. Ellis, Oriol Nieto, Colin Raffel, Dawen Liang, Matt McVicar, Eric Battenberg, Juan Pablo Bello, Justin Salamon and Eric J. Humphrey. Their work appears in journals such as IEEE Signal Processing Magazine, IEEE/ACM Transactions on Audio Speech and Language Processing, Frontiers in Psychology, International Journal of Computer Vision and IEEE Signal Processing Letters.

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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