Demo Data from SIGIR 2026 / reviewers in the wild / expert
Harald Grohganz
dblp:136/0897 · also Harald G. Grohganz
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
0009-0003-4340-0215ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing › source separation
music source separation |
0.2 | 1 | 2013 | Score-informed audio decomposition and applications · ACM Multimedia 2013 |
Audio and music processing › source separation › music source separation
score-informed source separation |
0.2 | 1 | 2013 | Score-informed audio decomposition and applications · ACM Multimedia 2013 |
Audio and music processing
audio editing |
0.0 | 1 | 2013 | Score-informed audio decomposition and applications · ACM Multimedia 2013 |
Methods — techniques the papers use, named apart from their topics
score-informed source separation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Score-informed audio decomposition and applicationsabstractThe separation of different sound sources from polyphonic music recordings constitutes a complex task since one has to account for different musical and acoustical aspects. In the last years, various score-informed procedures have been suggested where musical cues such as pitch, timing, and track information are used to support the source separation process. In this paper, we discuss a framework for decomposing a given music recording into notewise audio events which serve as elementary building blocks. In particular, we introduce an interface that employs the additional score information to provide a natural way for a user to interact with these audio events. By simply selecting arbitrary note groups within the score a user can access, modify, or analyze corresponding events in a given audio recording. In this way, our framework not only opens up new ways for audio editing applications, but also serves as a valuable tool for evaluating and better understanding the results of source separation algorithms. Jonathan Driedger, Harald Grohganz, Thomas Prätzlich, Sebastian Ewert, Meinard Müller |
ACM Multimedia | 2 |