Kilian, Jürgen (2005):
Inferring Score Level Musical Information From Low-Level Musical Data.
Darmstadt, Technische Universität, TU Darmstadt,
[Ph.D. Thesis]
Abstract
This thesis is focussed on inferring score level information from low-level symbolic musical data. It gives an introduction into approaches for musical quantisation, tempo detection, voice separation, as well as key and meter detection or the inference of secondary score level information. The thesis introduces also new approaches based on pattern detection and statistical analysis for the core issues tempo detection and quantisation. For the voice separation problem the thesis introduces a now approach based on local search.
| Item Type: |
Ph.D. Thesis
|
| Erschienen: |
2005 |
| Creators: |
Kilian, Jürgen |
| Title: |
Inferring Score Level Musical Information From Low-Level Musical Data |
| Language: |
English |
| Abstract: |
This thesis is focussed on inferring score level information from low-level symbolic musical data. It gives an introduction into approaches for musical quantisation, tempo detection, voice separation, as well as key and meter detection or the inference of secondary score level information. The thesis introduces also new approaches based on pattern detection and statistical analysis for the core issues tempo detection and quantisation. For the voice separation problem the thesis introduces a now approach based on local search. |
| Place of Publication: |
Darmstadt |
| Publisher: |
Technische Universität |
| Uncontrolled Keywords: |
Computermusik, Tempo Erkennung, Quantisierung, Stimmentrennung, GUIDO Musiknotation |
| Divisions: |
20 Department of Computer Science |
| Date Deposited: |
17 Oct 2008 09:21 |
| URL / URN: |
urn:nbn:de:tuda-tuprints-5297 |
| License: |
only the rights of use according to UrhG |
| Refereed / Verteidigung / mdl. Prüfung: |
8 October 2004 |
| Alternative keywords: |
| Alternative keywords | Language |
|---|
| Computermusic, Quantisation, Tempo Detection, Voice Separation, GUIDO Music Notation | English |
|
| Alternative Abstract: |
| Alternative abstract | Language |
|---|
Diese Arbeit gibt eine Übersicht über die Kernprobleme bei der Konvertierung von symbolischen musikalischen Rohdaten in Partiturinformation: Tempo Erkennung, Quantisierung und Stimmentrennung. Neben diesen Kernproblemen werden auch Themen wie Takt- und Tonarterkennung bzw. die Erkennung von sekundauml;ren Partitur-Informationen behandelt. In der Arbeit werden fü die Kernprobleme Tempo-Erkennung und Quantisierung neue Konzepte vorgestellt, welche auf Mustererkennung und statistischer Analyse basieren. Für das Stimmentrennungproblem wird ein Verfahren basierend auf lokaler Suche vorgestellt. | German |
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