The objective of this research is to improve the analysis of musical sounds in comparison to traditional additive analysis, i.e. Fourier Analysis. Namely, the focus of this study is to improve the tracking of time-evolving partials. Traditional analysis methods assume constant amplitudes and frequencies over each successive frame in which a signal is analyzed. Tracking the time-evolution of these partials, however, can require the implementation of complex probabilistic techniques. This thesis presents an alternative method in which the Ambiguity Function, a distribution in both time and frequency, is used to create a clearer, more accurate representation that requires fewer complex methods to track partials. Through the use of a more accurate spectral representation and the inclusion of a chirp rate parameter, partials may be more readily followed based upon spectral parameters alone. This new method that is presented will build upon the traditional methods by first employing Fourier analysis to identify partials, and then utilizing the Analytic Signal and Ambiguity Function to improve individual spectral parameter estimations and partial tracking. The overall intent of this work is that through this method, one may create an improved spectral model that is more useful to musical analysis.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.83189 |
| Date | January 2005 |
| Creators | Kosek, Paul C. |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Arts (Faculty of Music.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002293419, proquestno: AAIMR22605, Theses scanned by UMI/ProQuest. |
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