Memory-Based Models of Melodic Analysis
Challenging the Gestalt Principles
Bibliographic Data
| ID | 5305010 |
|---|---|
| Authors | Rens Bod (corresponding author) |
| Year | 2002 |
| Volume | 31 |
| Issue | 1 |
| Pages | 27-36 |
| Publication date | 2002-03-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of New Music Research (JOURNAL) |
| Journal identifiers | ISSN: 0929-8215 • E-ISSN: 1744-5027 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1076/jnmr.31.1.27.8106 |
| OpenAlex | W2141380728 |
| Language | EN |
| Citations received | 16 |
| References cited | 2 |
We argue for a memory-based approach to music analysis which works with concrete musical experiences rather than with abstract rules or principles. New pieces of music are analyzed by combining fragments from structures of previously encountered pieces. The occurrence-frequencies of the fragments are used to determine the preferred analysis of a piece. We test some instances of this approach against a set of 1,000 manually annotated folksongs from the Essen Folksong Collection, yielding up to 85.9 % phrase accuracy. A qualitative analysis of our results indicates that there are grouping phenomena that challenge the commonly accepted Gestalt principles of proximity, similarity and parallelism. These grouping phenomena can neither be explained by other musical factors, such as meter and harmony. We argue that music perception may be much more memory-based than previously assumed. 1
Art · Cognitive science · Gestalt psychology · Linguistics · Melody · Musical · Natural language processing · Perception · Phrase · Speech recognition · Visual arts · Computer Science · Music and Audio Processing · Music Technology and Sound Studies · Neuroscience and Music Perception · Psychology · Artificial Intelligence
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Automatic Segmentation and Comparative Study of Motives in Eleven Folk Song Collections using Self-Organizing Maps and Multidimensional Mapping
A Robust Parser-Interpreter for Jazz Chord Sequences
Cognition-based Segmentation for Music Information Retrieval Systems
Harmonic clusters and tonal cadences
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| Unique citing works | 16 |
|---|---|
| Citations per year | 0,73 |
| Citation span | 2004 - 2023 (20) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 14 |