Recombinant Music: Using the Computer to Explore Musical Style
Computer - Special issue: Computer-generated music
Melodic matching techniques for large music databases
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Making Music with Algorithms: A Case-Study System
Computer Music Journal
Extracting patterns in music for composition via Markov chains
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Finding maximum-length repeating patterns in music databases
Multimedia Tools and Applications
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Composing with Algorithms: An Interview with David Cope
Computer Music Journal
True suffix tree approach for discovering non-trivial repeating patterns in a music object
Multimedia Tools and Applications
Proceedings of the 2008 ACM symposium on Applied computing
Pattern Recognition Approach for Music Style Identification Using Shallow Statistical Descriptors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Computer music composition is the dream of computer music researchers. In this paper, a top-down approach is investigated to discover the rules of musical composition from given music objects and to create a new music object of which style is similar to the given music objects based on the discovered composition rules. The proposed approach utilizes the data mining techniques in order to discover the styled rules of music composition characterized by music structures, melody styles and motifs. A new music object is generated based on the discovered rules. To measure the effectiveness of the proposed approach in computer music composition, a method similar to the Turing test was adopted to test the differences between the machine-generated and human-composed music. Experimental results show that it is hard to distinguish between them. The other experiment showed that the style of generated music is similar to that of the given music objects.