Hochreiter, Ronald. 2006. Audible Convergence for Optimal Base Melody Extension with Statistical Genre-Specific Interval Distance Evaluation. Lecture Notes in Computer Science 3907 712-716.
BibTeX
Abstract
In this paper, an evolutionary algorithm is used to calculate optimal extensions of a base melody line by statistical interval-distance minimiza- tion. Applying an evolutionary algorithm for solving such an optimiza- tion problem reveals the e®ect of audible convergence, when iterations of the optimization process, which represent sub-optimal melody lines, are combined to a musical piece. An example is provided to evaluate the algorithm, and to point out di®erences of the ¯nal score, when di®er- ent musical genres, represented by di®erent interval distance classi¯cation schemes, are applied.
Tags
Press 'enter' for creating the tagPublication's profile
Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Journal article |
Journal | Lecture Notes in Computer Science (LNCS) |
WU-Journal-Rating new | STRAT-C |
Language | English |
Title | Audible Convergence for Optimal Base Melody Extension with Statistical Genre-Specific Interval Distance Evaluation |
Volume | 3907 |
Year | 2006 |
Page from | 712 |
Page to | 716 |
Reviewed? | Y |
URL | http://homepage.univie.ac.at/ronald.hochreiter/pub/preprint/h-audconv-full.pdf |
Associations
- People
- Hochreiter, Ronald (Details)
- Organization
- Institute for Statistics and Mathematics IN (Details)