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Modelling the Perception of Musical Sequences with Self-organizing Neural Networks

 

作者: MICHAELP. A. PAGE,  

 

期刊: Connection Science  (Taylor Available online 1994)
卷期: Volume 6, issue 2-3  

页码: 223-246

 

ISSN:0954-0091

 

年代: 1994

 

DOI:10.1080/09540099408915725

 

出版商: Taylor & Francis Group

 

关键词: Music;sequence;expectation;self-organizing;neural network;mask-ing-field;hierarchy

 

数据来源: Taylor

 

摘要:

A brief review of studies into the psychology of melody perception leads to the conclusion that melodies are represented in long-term memory as sequences of specific items, either intervals or scale notes; the latter representation is preferred. Previous connectionist models of musical-sequence learning are discussed and criticized as models of perception. The Cohen— Grossberg masking field (Cohen & Grossberg, 1987) is described and it is shown how it can be used to generate melodic expectations when incorporated within an adaptive resonance architecture. An improved formulation, the SONNET 1 network (Nigrin, 1990, 1992), is described in detail and modifications are suggested. The network is tested on its ability to learn short melodic phrases taken from a set of simple melodies, before being applied to the learning of the melodies themselves. Mechanisms are suggested for sequence recognition and sequence recall. The advantages of this approach to sequence learning are discussed.

 

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