Matt McVicar

3.3k total citations · 1 hit paper
23 papers, 1.9k citations indexed

About

Matt McVicar is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Matt McVicar has authored 23 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Signal Processing, 12 papers in Computer Vision and Pattern Recognition and 6 papers in Artificial Intelligence. Recurrent topics in Matt McVicar's work include Music and Audio Processing (17 papers), Music Technology and Sound Studies (12 papers) and Speech and Audio Processing (9 papers). Matt McVicar is often cited by papers focused on Music and Audio Processing (17 papers), Music Technology and Sound Studies (12 papers) and Speech and Audio Processing (9 papers). Matt McVicar collaborates with scholars based in United Kingdom, United States and Japan. Matt McVicar's co-authors include Daniel P. W. Ellis, Colin Raffel, Dawen Liang, Brian McFee, Oriol Nieto, Eric Battenberg, Tijl De Bie, Raúl Santos‐Rodríguez, Yizhao Ni and Masataka Goto and has published in prestigious journals such as Pattern Recognition Letters, IEEE Transactions on Audio Speech and Language Processing and IEEE/ACM Transactions on Audio Speech and Language Processing.

In The Last Decade

Matt McVicar

22 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

librosa: Audio and Music Signal Analysis in Python

2015 1.7k citations Brian McFee, Colin Raffel et al. Proceedings of the Python in Science Conferences profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Matt McVicar United Kingdom	9	1.4k	647	548	300	271	23	1.9k
Eric Battenberg United States	8	1.3k 0.9×	552 0.9×	587 1.1×	296 1.0×	225 0.8×	15	1.9k
Oriol Nieto United States	15	1.8k 1.3×	893 1.4×	616 1.1×	302 1.0×	332 1.2×	34	2.3k
Brian McFee United States	23	2.3k 1.6×	1.6k 2.4×	987 1.8×	306 1.0×	387 1.4×	57	3.3k
Rif A. Saurous United States	12	2.2k 1.5×	901 1.4×	2.0k 3.7×	280 0.9×	166 0.6×	16	3.5k
Sourish Chaudhuri United States	8	1.1k 0.8×	695 1.1×	516 0.9×	155 0.5×	124 0.5×	20	1.7k
Shawn Hershey United States	4	967 0.7×	664 1.0×	442 0.8×	152 0.5×	122 0.5×	5	1.5k
Marvin Ritter United States	5	1.3k 0.9×	849 1.3×	630 1.1×	98 0.3×	158 0.6×	7	1.9k
Jort F. Gemmeke Belgium	20	3.4k 2.4×	1.5k 2.4×	1.7k 3.1×	287 1.0×	349 1.3×	85	4.5k
Aren Jansen United States	24	3.2k 2.3×	1.5k 2.3×	2.2k 3.9×	373 1.2×	305 1.1×	68	4.6k
Qiuqiang Kong United Kingdom	22	1.4k 1.0×	709 1.1×	615 1.1×	50 0.2×	120 0.4×	62	1.8k

Countries citing papers authored by Matt McVicar

Since Specialization

Citations

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

Fields of papers citing papers by Matt McVicar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matt McVicar

This figure shows the co-authorship network connecting the top 25 collaborators of Matt McVicar. A scholar is included among the top collaborators of Matt McVicar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matt McVicar. Matt McVicar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

McVicar, Matt, et al.. (2018). StructureNet: Inducing Structure in Generated Melodies. International Symposium/Conference on Music Information Retrieval. 725–731. 17 indexed citations

McVicar, Matt, Raúl Santos‐Rodríguez, & Tijl De Bie. (2016). Learning to separate vocals from polyphonic mixtures via ensemble methods and structured output prediction. Bristol Research (University of Bristol). 15. 450–454. 3 indexed citations

McVicar, Matt, et al.. (2016). SuMoTED: An intuitive edit distance between rooted unordered uniquely-labelled trees. Pattern Recognition Letters. 79. 52–59. 6 indexed citations

McFee, Brian, Colin Raffel, Dawen Liang, et al.. (2015). librosa: Audio and Music Signal Analysis in Python. Proceedings of the Python in Science Conferences. 18–24. 1676 indexed citations breakdown →

McFee, Brian, Matt McVicar, Colin Raffel, et al.. (2015). librosa: 0.4.1. Zenodo (CERN European Organization for Nuclear Research). 7 indexed citations

McVicar, Matt, et al.. (2015). Supply and demand of independent UK music artists on the web. 1–2.

McVicar, Matt, Satoru Fukayama, & Masataka Goto. (2015). AutoGuitarTab: Computer-aided Composition of Rhythm \& Lead Guitar Parts in the Tablature Space. IEEE/ACM Transactions on Audio Speech and Language Processing. 1–1. 2 indexed citations

McFee, Brian, Matt McVicar, Colin Raffel, et al.. (2015). librosa: v0.4.0. Zenodo (CERN European Organization for Nuclear Research). 14 indexed citations

Santos‐Rodríguez, Raúl, et al.. (2015). Trend Extraction on Twitter Time Series for Music Discovery. Bristol Research (University of Bristol). 2 indexed citations

10.

McVicar, Matt, Satoru Fukayama, & Masataka Goto. (2014). AutoLeadGuitar: Automatic generation of guitar solo phrases in the tablature space. 28. 599–604. 8 indexed citations

11.

McFee, Brian, et al.. (2014). librosa: v0.3.1. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

12.

McVicar, Matt, Raúl Santos‐Rodríguez, Yizhao Ni, & Tijl De Bie. (2014). Automatic Chord Estimation from Audio: A Review of the State of the Art. IEEE/ACM Transactions on Audio Speech and Language Processing. 22(2). 556–575. 40 indexed citations

13.

McVicar, Matt, Daniel P. W. Ellis, & Masataka Goto. (2014). Leveraging repetition for improved automatic lyric transcription in popular music. 3117–3121. 23 indexed citations

14.

McVicar, Matt & Tijl De Bie. (2012). CCA and a Multi-way Extension for Investigating Common Components between Audio, Lyrics and Tags.. Ghent University Academic Bibliography (Ghent University). 53–68. 2 indexed citations

15.

Ni, Yizhao, Matt McVicar, Raúl Santos‐Rodríguez, & Tijl De Bie. (2012). An End-to-End Machine Learning System for Harmonic Analysis of Music. IEEE Transactions on Audio Speech and Language Processing. 20(6). 1771–1783. 35 indexed citations

16.

Ni, Yizhao, Matt McVicar, Raúl Santos‐Rodríguez, & Tijl De Bie. (2012). Using Hyper-Genre Training To Explore Genre Information For Automatic Chord Estimation.. Ghent University Academic Bibliography (Ghent University). 109–114. 4 indexed citations

17.

McVicar, Matt, et al.. (2011). Mining The Correlation Between Lyrical And Audio Features And The Emergence Of Mood.. Ghent University Academic Bibliography (Ghent University). 783–788. 22 indexed citations

18.

McVicar, Matt, Yizhao Ni, Raúl Santos‐Rodríguez, & Tijl De Bie. (2011). Using Online Chord Databases to Enhance Chord Recognition. Journal of New Music Research. 40(2). 139–152. 5 indexed citations

19.

McVicar, Matt, Yizhao Ni, Tijl De Bie, & Raúl Santos‐Rodríguez. (2011). Leveraging Noisy Online Databases For Use In Chord Recognition.. Zenodo (CERN European Organization for Nuclear Research). 5 indexed citations

20.

McVicar, Matt & Tijl De Bie. (2010). Enhancing chord recognition accuracy using web resources. 41–44. 3 indexed citations

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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