Towards a Computational Model of Melody Identification in Polyphonic Music

被引：0

作者：

Madsen, Soren Tjagvad ^{[1
]}

Widmer, Gerhard ^{[2
]}

机构：

[1] Austrian Res Inst Artificial Intelligence, Vienna, Austria

[2] Johannes Kepler Univ Linz, Dept Computat Percept, Linz, Austria

来源：

20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2007年

关键词：

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：

This paper presents first steps towards a simple, robust computational model of automatic melody identification. Based on results from music psychology that indicate a relationship between melodic complexity and a listener's attention, we postulate a relationship between musical complexity and the probability of a musical line to be perceived as the melody. We introduce a simple measure of melodic complexity, present an algorithm for predicting the most likely melody note at any point in a piece, and show experimentally that this simple approach works surprisingly well in rather complex music.

引用

页码：459 / 464

页数：6

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