Music Generation with Relation Join
| Autor: | Xiuyan Ni, Robert M. Haralick, Ligon Liu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
education.field_of_study
Theoretical computer science Database Relation (database) Computer science Population 020207 software engineering Harmonic (mathematics) Context (language use) 02 engineering and technology computer.software_genre Information theory 01 natural sciences 010104 statistics & probability 0202 electrical engineering electronic engineering information engineering Join (sigma algebra) 0101 mathematics Construct (philosophy) education Projection (set theory) computer |
| Zdroj: | Bridging People and Sound ISBN: 9783319677378 CMMR |
| DOI: | 10.1007/978-3-319-67738-5_3 |
| Popis: | Given a data set taken over a population, the question of how can we construct possible explanatory models for the interactions and dependencies in the population is a discovery question. Projection and Relation Join is a way of addressing this question in a non-deterministic context with mathematical relations. In this paper, we apply projection and relation join to music harmonic sequences to generate new sequences in a given composer or genre style. Instead of first learning the patterns, and then making replications as early music generation work did, we introduce a completely new data driven methodology to generate music. Then we discuss exploring the difference between the original music and synthetic music sequences using information theory based techniques. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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