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Documents authored by Wiggins, Geraint A.

Document
DOI: 10.4230/DagSemProc.09051.1
09051 Abstracts Collection – Knowledge representation for intelligent music processing

Authors: Eleanor Selfridge-Field, Frans Wiering, and Geraint A. Wiggins

Published in: Dagstuhl Seminar Proceedings, Volume 9051, Knowledge representation for intelligent music processing (2009)

Abstract
From the twenty-fifth to the thirtieth of January, 2009, the Dagstuhl Seminar 09051 on ``Knowledge representation for intelligent music processing'' was held in Schloss Dagstuhl~--~Leibniz Centre for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations and demos given during the seminar as well as plenary presentations, reports of workshop discussions, results and ideas are put together in this paper. The first section describes the seminar topics and goals in general, followed by plenary `stimulus' papers, followed by reports and abstracts arranged by workshop followed finally by some concluding materials providing views of both the seminar itself and also forward to the longer-term goals of the discipline. Links to extended abstracts, full papers and supporting materials are provided, if available. The organisers thank David Lewis for editing these proceedings.
Cite as

Eleanor Selfridge-Field, Frans Wiering, and Geraint A. Wiggins. 09051 Abstracts Collection – Knowledge representation for intelligent music processing. In Knowledge representation for intelligent music processing. Dagstuhl Seminar Proceedings, Volume 9051, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{selfridgefield_et_al:DagSemProc.09051.1,
  author =	{Selfridge-Field, Eleanor and Wiering, Frans and Wiggins, Geraint A.},
  title =	{{09051 Abstracts Collection – Knowledge representation for intelligent music processing}},
  booktitle =	{Knowledge representation for intelligent music processing},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9051},
  editor =	{Eleanor Selfridge-Field and Frans Wiering and Geraint A. Wiggins},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09051.1},
  URN =		{urn:nbn:de:0030-drops-19722},
  doi =		{10.4230/DagSemProc.09051.1},
  annote =	{Keywords: Music representation, music encoding, digital music edition, Music Information Retrieval, intelligent music processing, music informatics, data formats, data interchange, music collections, audio, MIDI, MEI, TEI, humdrum}
}
Document
DOI: 10.4230/DagSemProc.09051.3
Case Study ``Beatles Songs'' – What can be Learned from Unreliable Music Alignments?

Authors: Sebastian Ewert, Meinard Müller, Daniel Müllensiefen, Michael Clausen, and Geraint A. Wiggins

Published in: Dagstuhl Seminar Proceedings, Volume 9051, Knowledge representation for intelligent music processing (2009)

Abstract
As a result of massive digitization efforts and the world wide web, there is an exploding amount of available digital data describing and representing music at various semantic levels and in diverse formats. For example, in the case of the Beatles songs, there are numerous recordings including an increasing number of cover songs and arrangements as well as MIDI data and other symbolic music representations. The general goal of music synchronization is to align the multiple information sources related to a given piece of music. This becomes a difficult problem when the various representations reveal significant differences in structure and polyphony, while exhibiting various types of artifacts. In this paper, we address the issue of how music synchronization techniques are useful for automatically revealing critical passages with significant difference between the two versions to be aligned. Using the corpus of the Beatles songs as test bed, we analyze the kind of differences occurring in audio and MIDI versions available for the songs.
Cite as

Sebastian Ewert, Meinard Müller, Daniel Müllensiefen, Michael Clausen, and Geraint A. Wiggins. Case Study ``Beatles Songs'' – What can be Learned from Unreliable Music Alignments?. In Knowledge representation for intelligent music processing. Dagstuhl Seminar Proceedings, Volume 9051, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{ewert_et_al:DagSemProc.09051.3,
  author =	{Ewert, Sebastian and M\"{u}ller, Meinard and M\"{u}llensiefen, Daniel and Clausen, Michael and Wiggins, Geraint A.},
  title =	{{Case Study ``Beatles Songs'' – What can be Learned from Unreliable Music Alignments?}},
  booktitle =	{Knowledge representation for intelligent music processing},
  pages =	{1--16},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9051},
  editor =	{Eleanor Selfridge-Field and Frans Wiering and Geraint A. Wiggins},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09051.3},
  URN =		{urn:nbn:de:0030-drops-19640},
  doi =		{10.4230/DagSemProc.09051.3},
  annote =	{Keywords: MIDI, audio, music synchronization, multimodal, music collections, Beatles songs}
}
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