Timbre analysis by synthesis: representations, imitations, and variants for musical composition
Representations of musical signals
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Automated synthesis of analog electrical circuits by means ofgenetic programming
IEEE Transactions on Evolutionary Computation
Solutions for distributed musical instruments on the web
PPPJ '02/IRE '02 Proceedings of the inaugural conference on the Principles and Practice of programming, 2002 and Proceedings of the second workshop on Intermediate representation engineering for virtual machines, 2002
Interactive spatialization and sound design using an evolutionary system
NIME '07 Proceedings of the 7th international conference on New interfaces for musical expression
Creating Soundscapes Using Evolutionary Spatial Control
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Parallel evolutionary optimization of digital sound synthesis parameters
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Path of patches: implementing an evolutionary soundscape art installation
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Convergence synthesis of dynamic frequency modulation tones using an evolution strategy
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Application of an artificial immune system in a compositional timbre design technique
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
| Hi-index | 0.00 |
A mathematical model for interactive sound synthesis based on the application of Genetic Algorithms (GA) is presented. The Evolutionary Sound Synthesis Method (ESSynth) generates sequences of waveform variants by the application of genetic operators on an initial population of waveforms. We describe how the waveforms can be treated as genetic code, the fitness evaluation methodology and how genetic operations such as crossover and mutation are used to produce generations of waveforms. Finally, we discuss the results evaluating the generated sounds.