Name
Abstract | ||
|---|---|---|
Music is an expressive form of communication often used to convey emotion in scenarios where words are not enough. Part of this information lies in the composition where well-defined language exists. However, a significant amount of information is added during a performance as the musician interprets the composition. The performer injects expressiveness into the written score through variations of different properties such as dynamics and tempo. In this paper, we describe a model that can learn to perform sheet music. Our research concludes that the generated performances are indistinguishable from a human performance, thereby passing a test in the spirit of a musical Turing test. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Sound | Computer science,Musical,Turing test,Musical composition,Speech recognition,Performing arts,Linguistics,Expressivity |
DocType | Volume | Citations |
Journal | abs/1708.03535 | 3 |
PageRank | References | Authors |
0.45 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iman Malik | 1 | 3 | 0.45 |
| carl henrik ek | 2 | 327 | 30.76 |