Automatic music classification with jMIR
C McKay - 2010 - escholarship.mcgill.ca
La classification automatique de la musique est un vaste domaine de recherche,
multidisciplinaire par nature, et qui donne lieu à des avancées significatives tant du point de …
multidisciplinaire par nature, et qui donne lieu à des avancées significatives tant du point de …
[PDF][PDF] The potential for automatic assessment of trumpet tone quality.
T Knight, F Upham, I Fujinaga - ISMIR, 2011 - Citeseer
The goal of this study was to examine the possibility of training machine learning algorithms
to differentiate between the performance of good notes and bad notes. Four trumpet players …
to differentiate between the performance of good notes and bad notes. Four trumpet players …
Improving automatic music classification performance by extracting features from different types of data
C McKay, I Fujinaga - Proceedings of the international conference on …, 2010 - dl.acm.org
This paper discusses two sets of automatic musical genre classification experiments.
Promising research directions are then proposed based on the results of these experiments …
Promising research directions are then proposed based on the results of these experiments …
Analysis of trumpet tone quality using machine learning and audio feature selection
T Knight - 2012 - escholarship.mcgill.ca
This work examines which audio features, the components of recorded sound, are most
relevant to trumpet tone quality by using classification and feature selection. A total of 10 …
relevant to trumpet tone quality by using classification and feature selection. A total of 10 …