Name
Abstract | ||
|---|---|---|
In this paper, we address the problem of automated music synthesis using deep neural networks and ask whether neural networks are capable of realizing timing, pitch accuracy and pattern generalization for automated music generation when processing raw audio data. To this end, we present a proof of concept and build a recurrent neural network architecture capable of generalizing appropriate musical raw audio tracks. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-01424-7_14 | ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2018, PT III |
Keywords | Field | DocType |
Music synthesis, Recurrent neural networks | Architecture,Ask price,Computer science,End-to-end principle,Generalization,Recurrent neural network,Speech recognition,Raw audio format,Proof of concept,Artificial intelligence,Artificial neural network,Machine learning | Conference |
Volume | ISSN | Citations |
11141 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manfred Eppe | 1 | 63 | 11.60 |
| Tayfun Alpay | 2 | 5 | 3.15 |
| Stefan Wermter | 3 | 1100 | 151.62 |