{"title":"Xenakis随机合成的物理启发实现:扩散动态随机合成","authors":"Emilio L. Rojas;Rodrigo F. Cádiz","doi":"10.1162/comj_a_00606","DOIUrl":null,"url":null,"abstract":"Abstract This article presents an extension of Iannis Xenakis's Dynamic Stochastic Synthesis (DSS) called Diffusion Dynamic Stochastic Synthesis (DDSS). This extension solves a diffusion equation whose solutions can be used to map particle positions to amplitude values of several breakpoints in a waveform, following traditional concepts of DSS by directly shaping the waveform of a sound. One significant difference between DSS and DDSS is that the latter includes a drift in the Brownian trajectories that each breakpoint experiences through time. Diffusion Dynamic Stochastic Synthesis can also be used in other ways, such as to control the amplitude values of an oscillator bank using additive synthesis, shaping in this case the spectrum, not the waveform. This second modality goes against Xenakis's original desire to depart from classical Fourier synthesis. The results of spectral analyses of the DDSS waveform approach, implemented using the software environment Max, are discussed and compared with the results of a simplified version of DSS to which, despite the similarity in the overall form of the frequency spectrum, noticeable differences are found. In addition to the Max implementation of the basic DDSS algorithm, a MIDI-controlled synthesizer is also presented here. With DDSS we introduce a real physical process, in this case diffusion, into traditional stochastic synthesis. This sort of sonification can suggest models of sound synthesis that are more complex and grounded in physical concepts.","PeriodicalId":50639,"journal":{"name":"Computer Music Journal","volume":"45 2","pages":"48-66"},"PeriodicalIF":0.4000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Physically Inspired Implementation of Xenakis's Stochastic Synthesis: Diffusion Dynamic Stochastic Synthesis\",\"authors\":\"Emilio L. Rojas;Rodrigo F. Cádiz\",\"doi\":\"10.1162/comj_a_00606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This article presents an extension of Iannis Xenakis's Dynamic Stochastic Synthesis (DSS) called Diffusion Dynamic Stochastic Synthesis (DDSS). This extension solves a diffusion equation whose solutions can be used to map particle positions to amplitude values of several breakpoints in a waveform, following traditional concepts of DSS by directly shaping the waveform of a sound. One significant difference between DSS and DDSS is that the latter includes a drift in the Brownian trajectories that each breakpoint experiences through time. Diffusion Dynamic Stochastic Synthesis can also be used in other ways, such as to control the amplitude values of an oscillator bank using additive synthesis, shaping in this case the spectrum, not the waveform. This second modality goes against Xenakis's original desire to depart from classical Fourier synthesis. The results of spectral analyses of the DDSS waveform approach, implemented using the software environment Max, are discussed and compared with the results of a simplified version of DSS to which, despite the similarity in the overall form of the frequency spectrum, noticeable differences are found. In addition to the Max implementation of the basic DDSS algorithm, a MIDI-controlled synthesizer is also presented here. With DDSS we introduce a real physical process, in this case diffusion, into traditional stochastic synthesis. This sort of sonification can suggest models of sound synthesis that are more complex and grounded in physical concepts.\",\"PeriodicalId\":50639,\"journal\":{\"name\":\"Computer Music Journal\",\"volume\":\"45 2\",\"pages\":\"48-66\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Music Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/9931004/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Music Journal","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/9931004/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A Physically Inspired Implementation of Xenakis's Stochastic Synthesis: Diffusion Dynamic Stochastic Synthesis
Abstract This article presents an extension of Iannis Xenakis's Dynamic Stochastic Synthesis (DSS) called Diffusion Dynamic Stochastic Synthesis (DDSS). This extension solves a diffusion equation whose solutions can be used to map particle positions to amplitude values of several breakpoints in a waveform, following traditional concepts of DSS by directly shaping the waveform of a sound. One significant difference between DSS and DDSS is that the latter includes a drift in the Brownian trajectories that each breakpoint experiences through time. Diffusion Dynamic Stochastic Synthesis can also be used in other ways, such as to control the amplitude values of an oscillator bank using additive synthesis, shaping in this case the spectrum, not the waveform. This second modality goes against Xenakis's original desire to depart from classical Fourier synthesis. The results of spectral analyses of the DDSS waveform approach, implemented using the software environment Max, are discussed and compared with the results of a simplified version of DSS to which, despite the similarity in the overall form of the frequency spectrum, noticeable differences are found. In addition to the Max implementation of the basic DDSS algorithm, a MIDI-controlled synthesizer is also presented here. With DDSS we introduce a real physical process, in this case diffusion, into traditional stochastic synthesis. This sort of sonification can suggest models of sound synthesis that are more complex and grounded in physical concepts.
期刊介绍:
Computer Music Journal is published quarterly with an annual sound and video anthology containing curated music¹. For four decades, it has been the leading publication about computer music, concentrating fully on digital sound technology and all musical applications of computers. This makes it an essential resource for musicians, composers, scientists, engineers, computer enthusiasts, and anyone exploring the wonders of computer-generated sound.
Edited by experts in the field and featuring an international advisory board of eminent computer musicians, issues typically include:
In-depth articles on cutting-edge research and developments in technology, methods, and aesthetics of computer music
Reports on products of interest, such as new audio and MIDI software and hardware
Interviews with leading composers of computer music
Announcements of and reports on conferences and courses in the United States and abroad
Publication, event, and recording reviews
Tutorials, letters, and editorials
Numerous graphics, photographs, scores, algorithms, and other illustrations.