2 Search Results for "Leman, Marc"

Document
DOI: 10.4230/LIPIcs.SEA.2023.1
Engineering a Preprocessor for Symmetry Detection

Authors: Markus Anders, Pascal Schweitzer, and Julian Stieß

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
State-of-the-art solvers for symmetry detection in combinatorial objects are becoming increasingly sophisticated software libraries. Most of the solvers were initially designed with inputs from combinatorics in mind (nauty, bliss, Traces, dejavu). They excel at dealing with a complicated core of the input. Others focus on practical instances that exhibit sparsity. They excel at dealing with comparatively easy but extremely large substructures of the input (saucy). In practice, these differences manifest in significantly diverging performances on different types of graph classes. We engineer a preprocessor for symmetry detection. The result is a tool designed to shrink sparse, large substructures of the input graph. On most of the practical instances, the preprocessor improves the overall running time significantly for many of the state-of-the-art solvers. At the same time, our benchmarks show that the additional overhead is negligible. Overall we obtain single algorithms with competitive performance across all benchmark graphs. As such, the preprocessor bridges the disparity between solvers that focus on combinatorial graphs and large practical graphs. In fact, on most of the practical instances the combined setup significantly outperforms previous state-of-the-art.
Cite as

Markus Anders, Pascal Schweitzer, and Julian Stieß. Engineering a Preprocessor for Symmetry Detection. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 1:1-1:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{anders_et_al:LIPIcs.SEA.2023.1,
  author =	{Anders, Markus and Schweitzer, Pascal and Stie{\ss}, Julian},
  title =	{{Engineering a Preprocessor for Symmetry Detection}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{1:1--1:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.1},
  URN =		{urn:nbn:de:0030-drops-183511},
  doi =		{10.4230/LIPIcs.SEA.2023.1},
  annote =	{Keywords: graph isomorphism, automorphism groups, symmetry detection, preprocessors}
}
Document
DOI: 10.4230/DagSemProc.06171.3
A User-Oriented Approach to Music Information Retrieval

Authors: Micheline Lesaffre, Marc Leman, and Jean-Pierre Martens

Published in: Dagstuhl Seminar Proceedings, Volume 6171, Content-Based Retrieval (2006)

Abstract
Search and retrieval of specific musical content (e.g. emotion, melody) has become an important aspect of system development but only little research is user-oriented. The success of music information retrieval technology primarily depends on both assessing and meeting the needs of its users. Potential users of music information retrieval systems, however, draw upon various ways of expressing themselves. But, who are the potential users of MIR systems and how would they describe music qualities? High-level concepts contribute to the definition of meaning in music. How can we measure meaning and emotion in music? How can we define the higher-order understanding of features of music that the average users share? Information on listener’s perception of qualities of music is needed to make automated access to music content attractive to system users. The emphasis of our investigation is on a user-oriented approach to the semantic description of music. We report the results of an experiment that explores how users perceive affects in music, and what structural descriptions of music best characterize their understanding of music expression. 79 potential users of music information retrieval systems rated different sets of adjectives, while they were listening to 160 pieces of real music. The subject group (79) was recruited amongst 774 participants in a large survey on the music background, habits and interests, preferred genres, taste and favourite titles of people who are willing to use interactive music systems. Moreover, the stimuli used reflected the musical taste of the average participant in the large survey (774). The study reveals that perceived qualities of music are affected by the profile of the user. Significant subject dependencies are found for age, music expertise, musicianship, broadness of taste and familiarity with classical music. Furthermore, interesting relationships are discovered between expressive and structural features. Analyses show that the targeted population most unanimously agrees on loudness and tempo, whilst less unanimity was found for timbre and articulation. Finally, our findings are tested and validated by means of a demo of a semantic music recommender system prototype that supports the querying of a music database by semantic descriptors for affect, structure and motion. The system, that recommends music from a relational database containing the quality ratings provided by the participants, illustrates the potential of a user-dependent and emotion-based retrieval of music.
Cite as

Micheline Lesaffre, Marc Leman, and Jean-Pierre Martens. A User-Oriented Approach to Music Information Retrieval. In Content-Based Retrieval. Dagstuhl Seminar Proceedings, Volume 6171, pp. 1-11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2006)

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@InProceedings{lesaffre_et_al:DagSemProc.06171.3,
  author =	{Lesaffre, Micheline and Leman, Marc and Martens, Jean-Pierre},
  title =	{{A User-Oriented Approach to Music Information Retrieval}},
  booktitle =	{Content-Based Retrieval},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6171},
  editor =	{Tim Crawford and Remco C. Veltkamp},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06171.3},
  URN =		{urn:nbn:de:0030-drops-6509},
  doi =		{10.4230/DagSemProc.06171.3},
  annote =	{Keywords: Semantic description, user studies, music information retrieval}
}
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