A machine learning approach to two-voice counterpoint composition

被引：10

作者：

Adiloglu, Kamil

Alpaslan, Ferda N. ^{[1
]}

机构：

[1] Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey

[2] Univ Technol Berlin, D-10587 Berlin, Germany

来源：

KNOWLEDGE-BASED SYSTEMS | 2007年 / 20卷 / 03期

关键词：

algorithmic composition; artificial neural networks; counterpoint; pitch; duration;

D O I：

10.1016/j.knosys.2006.04.018

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Algorithmic composition of musical pieces is one of the most popular areas of computer aided music research. Various attempts have been made successfully in the area of music composition. Artificial intelligence methods have been extensively applied in this area. Representation of musical pieces in a computer-understand able form plays an important role in computer aided music research. This paper presents a neural network-based knowledge representation schema for representing notes, melodies, and time in first species counterpoint pieces. A musical note is composed of pitch and duration in this representation schema. The proposed representation technique was tested using the back-propagation algorithm to generate two-voice counterpoint pieces. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：300 / 309

页数：10