Douglas Turnbull

2.5k total citations
36 papers, 1.7k citations indexed

About

Douglas Turnbull is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Douglas Turnbull has authored 36 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Signal Processing, 24 papers in Computer Vision and Pattern Recognition and 10 papers in Artificial Intelligence. Recurrent topics in Douglas Turnbull's work include Music and Audio Processing (32 papers), Music Technology and Sound Studies (17 papers) and Speech and Audio Processing (10 papers). Douglas Turnbull is often cited by papers focused on Music and Audio Processing (32 papers), Music Technology and Sound Studies (17 papers) and Speech and Audio Processing (10 papers). Douglas Turnbull collaborates with scholars based in United States, Singapore and Canada. Douglas Turnbull's co-authors include Gert Lanckriet, Luke Barrington, Youngmoo E. Kim, David Torres-Moreno, Erik M. Schmidt, Thorsten Joachims, Shuo Chen, Charles Elkan, Brandon G. Morton and Jeffrey J. Scott and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Audio Speech and Language Processing.

In The Last Decade

Douglas Turnbull

35 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Douglas Turnbull United States 19 1.2k 992 502 322 237 36 1.7k
Roger B. Dannenberg United States 25 1.6k 1.4× 1.6k 1.6× 394 0.8× 567 1.8× 158 0.7× 165 2.4k
Paul Lamere United States 14 890 0.8× 716 0.7× 636 1.3× 185 0.6× 302 1.3× 28 1.5k
Takuichi Nishimura Japan 14 724 0.6× 607 0.6× 339 0.7× 133 0.4× 221 0.9× 84 1.4k
Bryan Pardo United States 25 1.5k 1.3× 943 1.0× 405 0.8× 283 0.9× 102 0.4× 127 1.9k
Perfecto Herrera Spain 26 2.2k 1.9× 1.8k 1.8× 494 1.0× 725 2.3× 270 1.1× 142 2.8k
Peter Knees Austria 21 943 0.8× 856 0.9× 339 0.7× 191 0.6× 204 0.9× 92 1.2k
Brian Whitman United States 11 879 0.8× 726 0.7× 353 0.7× 141 0.4× 149 0.6× 23 1.2k
Joan Serrà Spain 20 1.0k 0.9× 758 0.8× 325 0.6× 290 0.9× 72 0.3× 81 1.4k
Erik M. Schmidt United States 20 814 0.7× 483 0.5× 494 1.0× 393 1.2× 22 0.1× 55 1.5k
Rebecca Fiebrink United Kingdom 18 335 0.3× 530 0.5× 213 0.4× 255 0.8× 50 0.2× 76 1.0k

Countries citing papers authored by Douglas Turnbull

Since Specialization
Citations

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

Fields of papers citing papers by Douglas Turnbull

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Douglas Turnbull

This figure shows the co-authorship network connecting the top 25 collaborators of Douglas Turnbull. A scholar is included among the top collaborators of Douglas Turnbull 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 Douglas Turnbull. Douglas Turnbull is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kauchak, David, et al.. (2023). Cross-Language Music Recommendation Exploration. 664–668.
2.
Joachims, Thorsten, et al.. (2020). Exploring acoustic similarity for novel music recommendation. Zenodo (CERN European Organization for Nuclear Research). 583–589. 2 indexed citations
3.
Turnbull, Douglas, et al.. (2018). SLIONS. 1679–1687. 16 indexed citations
4.
Moore, Joshua L., Thorsten Joachims, & Douglas Turnbull. (2014). Taste Space Versus The World: An Embedding Analysis Of Listening Habits And Geography.. Digital Collections - Ithaca College Library (Ithaca College). 439–444. 7 indexed citations
5.
Chen, Shuo, et al.. (2012). Playlist prediction via metric embedding. 714–722. 175 indexed citations
6.
Turnbull, Douglas, et al.. (2010). Exploring 'Artist Image' Using Content-Based Analysis Of Promotional Photos. The Journal of the Abraham Lincoln Association. 2010. 5 indexed citations
7.
Kim, Youngmoo E., Erik M. Schmidt, Raymond Migneco, et al.. (2010). Music emotion recognition: A state of the art review. Digital Collections - Ithaca College Library (Ithaca College). 255. 239 indexed citations
8.
Wicentowski, Richard, et al.. (2009). Using Regression To Combine Data Sources For Semantic Music Discovery.. Zenodo (CERN European Organization for Nuclear Research). 405–410. 6 indexed citations
9.
Turnbull, Douglas, et al.. (2009). Using Artist Similarity To Propagate Semantic Information.. Zenodo (CERN European Organization for Nuclear Research). 375–380. 25 indexed citations
10.
Barrington, Luke, Douglas Turnbull, & Gert Lanckriet. (2008). AUTO-TAGGING MUSIC CONTENT WITH SEMANTIC MULTINOMIALS. 3 indexed citations
11.
Turnbull, Douglas, Luke Barrington, & Gert Lanckriet. (2008). Five Approaches To Collecting Tags For Music.. Zenodo (CERN European Organization for Nuclear Research). 907. 225–230. 67 indexed citations
12.
Elkan, Charles, Gert Lanckriet, & Douglas Turnbull. (2008). Design and development of a semantic music discovery engine. 4 indexed citations
13.
Turnbull, Douglas, Luke Barrington, David Torres-Moreno, & Gert Lanckriet. (2008). Semantic Annotation and Retrieval of Music and Sound Effects. IEEE Transactions on Audio Speech and Language Processing. 16(2). 467–476. 331 indexed citations
14.
Barrington, Luke, et al.. (2008). Combining Feature Kernels For Semantic Music Retrieval.. Zenodo (CERN European Organization for Nuclear Research). 23 indexed citations
15.
Barrington, Luke, Antoni B. Chan, Douglas Turnbull, & Gert Lanckriet. (2007). Audio Information Retrieval using Semantic Similarity. II–725. 56 indexed citations
16.
Turnbull, Douglas, et al.. (2007). Exploring the Semantic Annotation and Retrieval of Sound. 3 indexed citations
17.
Turnbull, Douglas, Ruoran Liu, Luke Barrington, & Gert Lanckriet. (2007). A Game-Based Approach For Collecting Semantic Annotations Of Music.. Zenodo (CERN European Organization for Nuclear Research). 535–538. 72 indexed citations
18.
Turnbull, Douglas, Gert Lanckriet, Elias Pampalk, & Masataka Goto. (2007). A Supervised Approach For Detecting Boundaries In Music Using Difference Features And Boosting.. International Symposium/Conference on Music Information Retrieval. 51–54. 46 indexed citations
19.
Turnbull, Douglas, Luke Barrington, & Gert Lanckriet. (2006). Modeling Music And Words Using A Multi-Class Naïve Bayes Approach.. Zenodo (CERN European Organization for Nuclear Research). 254–259. 15 indexed citations
20.
Turnbull, Douglas & Charles Elkan. (2005). Fast recognition of musical genres using RBF networks. IEEE Transactions on Knowledge and Data Engineering. 17(4). 580–584. 72 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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