Demo Data from EDBT 2026 / reviewers in the wild / expert
Steven Hargreaves
dblp:97/10111
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
0000-0002-8926-6256ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing
music information retrieval |
0.1 | 1 | 2012 | Structural Segmentation of Multitrack Audio · IEEE Trans. Speech Audio Process. 2012 |
Audio and music processing › music structure analysis
structural segmentation |
0.1 | 1 | 2012 | Structural Segmentation of Multitrack Audio · IEEE Trans. Speech Audio Process. 2012 |
Methods — techniques the papers use, named apart from their topics
segmentation algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Structural Segmentation of Multitrack AudioabstractStructural segmentation of musical audio signals is one of many active areas of Music Information Retrieval (MIR) research. One aspect of this important topic which has so far received little attention though is the potential advantage to be gained by utilizing multitrack audio. This paper gives an overview of current segmentation techniques, and demonstrates that by applying a particular segmentation algorithm to multitrack data, rather than the usual case of fully mixed audio, we achieve a significant and quantifiable increase in accuracy when locating segment boundaries. Additionally, we provide details of a structurally annotated multitrack test set available for use by other researchers. Steven Hargreaves, Anssi Klapuri, Mark B. Sandler |
IEEE Trans. Speech Audio Process. | 1 |