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Harald Grohganz

dblp:136/0897 · also Harald G. Grohganz · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Audio and music processing › source separation
music source separation
0.212013
Score-informed audio decomposition and applications · ACM Multimedia 2013
Audio and music processing › source separation › music source separation
score-informed source separation
0.212013
Score-informed audio decomposition and applications · ACM Multimedia 2013
Audio and music processing
audio editing
0.012013
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
YearPublicationVenuePosition
2013 Score-informed audio decomposition and applications
abstract
The 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 Multimedia2