Composing music with Neural Networks and probabilistic Finite-State Machines

被引：0
|
作者：
Oliwa, Tomasz [1 ,2 ]
Wagner, Markus [1 ,2 ]
机构：
[1] Univ Georgia, Ctr Artificial Intelligence, Athens, GA 30602 USA
[2] University of Koblenz Landau, Inst Comp Sci, Koblenze, Germany
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS | 2008年 / 4974卷
关键词：
biological inspired music; music composition; representation techniques; comparative analysis; Time Delay Neural Networks; finite state machines; inductive learning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, biological (human) music composition systems based on Time Delay Neural Networks and Ward Nets and on a probabilistic Finite-State Machine will be presented. The systems acquire musical knowledge by inductive learning and are able to produce complete musical scores for multiple instruments and actual music in the MIDI format. The quality of our approaches is analyzed in objective and subjective manner with existing techniques.
引用
收藏
页码：503 / +
页数：2
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