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.
| 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 |
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}
GenMuse : An Evolutionary Creativity Enhancement Tool. / Salomoni, Massimo; Carter, Jenny.
Artificial Intelligence XXXVI: 39th SGAI International Conference on Artificial Intelligence, AI 2019, Cambridge, UK, December 17–19, 2019, Proceedings. ed. / Max Bramer; Miltos Petridis. Vol. LNAI 11927 Cham : Springer, Cham, 2019. p. 229-240 (Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence; Vol. LNCS 11927/LNAI 11927).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - GenMuse
T2 - An Evolutionary Creativity Enhancement Tool
AU - Salomoni, Massimo
AU - Carter, Jenny
PY - 2019/11/19
Y1 - 2019/11/19
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.
KW - Creativity
KW - Genetic Algorithms
KW - Neural networks
KW - Music
UR - http://www.scopus.com/inward/record.url?scp=85076954014&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-34885-4_18
DO - 10.1007/978-3-030-34885-4_18
M3 - Conference contribution
SN - 9783030348847
VL - LNAI 11927
T3 - Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence
SP - 229
EP - 240
BT - Artificial Intelligence XXXVI
A2 - Bramer, Max
A2 - Petridis, Miltos
PB - Springer, Cham
CY - Cham
ER -