The development of computer algorithms for music instrument identification and parameter extraction in digital audio signals is an active research field. A musician can listen to music and instantly identify different instruments and the timbres produced by various playing techniques. Creating software to allow computers to do the same is much more challenging. This thesis will use digital signal processing and machine learning techniques to differentiate snare drum timbres produced by different stroke positions and stroke techniques.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.81515 |
| Date | January 2004 |
| Creators | Tindale, Adam |
| 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: 002186209, proquestno: AAIMR06532, Theses scanned by UMI/ProQuest. |
Page generated in 0.002 seconds