Abstract
Creativity is often defined as the creation of something novel through the use of imagination. But for all artists, creativity is also the exploration of new and unknown areas within their specific art. Is it possible to stimulate creativity through a system that creates inspiring original music, and that is also able to learn the personal tastes of its user?
Within the project, an evolutionary approach was used in an attempt to stimulate musical creativity by supplying a composer with software that can compose short musical patterns called riffs. The software, called GenMuse, evolves populations of riffs, and makes use of a feed-forward artificial neural network to learn how to autonomously evaluate the evolved riffs to satisfy the tastes of the composer.
The results show that the approach is worthy of further investigation. The genetic algorithm produced interesting results that, according to our evaluation parameters, could be included “as is” in a musical composition, and the neural network was able to evaluate the riffs with a good success ratio.
Within the project, an evolutionary approach was used in an attempt to stimulate musical creativity by supplying a composer with software that can compose short musical patterns called riffs. The software, called GenMuse, evolves populations of riffs, and makes use of a feed-forward artificial neural network to learn how to autonomously evaluate the evolved riffs to satisfy the tastes of the composer.
The results show that the approach is worthy of further investigation. The genetic algorithm produced interesting results that, according to our evaluation parameters, could be included “as is” in a musical composition, and the neural network was able to evaluate the riffs with a good success ratio.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence XXXVI |
| Subtitle of host publication | 39th SGAI International Conference on Artificial Intelligence, AI 2019, Cambridge, UK, December 17–19, 2019, Proceedings |
| Editors | Max Bramer, Miltos Petridis |
| Place of Publication | Cham |
| Publisher | Springer, Cham |
| Pages | 229-240 |
| Number of pages | 12 |
| Volume | LNAI 11927 |
| ISBN (Electronic) | 9783030348854 |
| ISBN (Print) | 9783030348847 |
| DOIs | |
| Publication status | Published - 19 Nov 2019 |
| Event | 39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence - Peterhouse College, Cambridge, Cambridge, United Kingdom Duration: 17 Dec 2019 → 19 Dec 2019 Conference number: 39 http://www.bcs-sgai.org/ai2019/?section=call |
Publication series
| Name | Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence |
|---|---|
| Publisher | Springer |
| Volume | LNCS 11927/LNAI 11927 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence |
|---|---|
| Abbreviated title | AI 2019 |
| Country | United Kingdom |
| City | Cambridge |
| Period | 17/12/19 → 19/12/19 |
| Internet address |