Multi-Dimensional motivic pattern extraction founded on adaptive redundancy filtering
Bibliographic Data
| ID | 5304384 |
|---|---|
| Authors | Olivier Lartillot (0000-0002-3294-2719, University of Jyväskylä, corresponding author) |
| Year | 2005 |
| Volume | 34 |
| Issue | 4 |
| Pages | 375-393 |
| Publication date | 2005-12-01 |
| 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 | 10.1080/09298210600578246 |
| OpenAlex | W2045904258 |
| Language | EN |
| Citations received | 9 |
| References cited | 13 |
We present a computational model for discovering repeated patterns in symbolic representations of monodic music. Patterns are discovered through an incremental adaptive identification along a multi-dimensional para-metric space. The difficulties of pattern discovery mainly come from combinatorial redundancies, that our model is able to control efficiently. A specificity relation is defined between pattern descriptions, unifying suffix and inclusion relations and enabling a filtering of redundant descriptions. Combinatorial proliferation caused by successive repetitions of patterns is managed using cyclic patterns. The modelling of these redundancy control mechanisms enables an automation of musicology-relevant analyses of musical databases. 1
Active listening · Ethnomusicology · Musical · Musicology · Sociology · Computer Science · Music and Audio Processing · Music Technology and Sound Studies · Neuroscience and Music Perception · Artificial Intelligence
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| Citations per year | 0.45 |
|---|---|
| Citation span | 2006 - 2025 (20) |
| Highly cited | No |