Abstract
This ongoing project describes neural network applications for helping musical composition using as inspiration the natural landscape contours. We propose supervised and unsupervised learning approaches, by using Back-Propagation-Through-Time (BPTT) and Self Organizing Maps (SOM) neural networks. In the supervised learning, the network learns certain aspects of musical structure by means of measure examples taken from melodies of the training set and uses these measures learned to compose new melodies using as input the extracted data of the landscapes contour. In the unsupervised learning, the network also uses measure examples as input during training and the extracted data of the landscapes contour in the composition stage. The obtained results show the viability of both approaches.
Original language | English |
---|---|
Title of host publication | SAC '08 |
Subtitle of host publication | Proceedings of the 2008 ACM symposium on Applied computing |
Publisher | Association for Computing Machinery (ACM) |
Pages | 1738-1742 |
Number of pages | 5 |
ISBN (Electronic) | 978-1-59593-753-7 |
DOIs | |
Publication status | Published - 16 Mar 2008 |
Externally published | Yes |
Event | The 2008 ACM Symposium on Applied Computing - Fortaleza, Brazil Duration: 16 Mar 2008 → 20 Mar 2008 https://dl.acm.org/doi/proceedings/10.1145/1363686 |
Conference
Conference | The 2008 ACM Symposium on Applied Computing |
---|---|
Abbreviated title | SAC '08 |
Country/Territory | Brazil |
City | Fortaleza |
Period | 16/03/08 → 20/03/08 |
Internet address |