Abstract
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.
| Language | English |
|---|---|
| Title of host publication | Proceedings of Specialist Group on Artificial Intellgence 2019 |
| Place of Publication | Cham |
| Publisher | Springer, Cham |
| Number of pages | 13 |
| Publication status | Accepted/In press - 2019 |
| Event | AI-2019 39th SGAI International Conference on 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 |
Conference
| Conference | AI-2019 39th SGAI International Conference on Artificial Intelligence |
|---|---|
| Abbreviated title | AI-2019 |
| Country | United Kingdom |
| City | Cambridge |
| Period | 17/12/19 → 19/12/19 |
| Internet address |
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GenMuse: an evolutionary creativity enhancement tool; MSc Intelligent Systems distance learning project. / Salomoni, Massimo; Carter, Jenny.
Proceedings of Specialist Group on Artificial Intellgence 2019. Cham : Springer, Cham, 2019.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - GenMuse: an evolutionary creativity enhancement tool;
T2 - MSc Intelligent Systems distance learning project
AU - Salomoni, Massimo
AU - Carter, Jenny
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - http://www.bcs-sgai.org/ai2019/
UR - https://link.springer.com/conference/sgai
M3 - Conference contribution
BT - Proceedings of Specialist Group on Artificial Intellgence 2019
PB - Springer, Cham
CY - Cham
ER -