Membership plan: Going Deeper | Topics: Sound Design
- The Fluid Corpus Manipulation project (FluCoMa) provides novel machine learning tools for digital composition.
- Unsupervised Machine Learning refers to finding patterns in data.
- FluCoMa objects analyze audio to find similar/different sounds, plot complex analyses in 2D space, and organize sound slices.
- This provides a vast array of creative possibilities for composition, sound design, and performance.
- Ted Moore from FluCoMa will guide you through the creative possibilities of Unsupervised Learning with FluCoMa Max Package.
- Basic experience of FluCoMa is advised before joining the workshop.
For example, it is strongly recommended that you have taken the free on-demand workshop Using Machine Learning Creatively via FluCoMa In Max.
Ted Moore (he / him) is a composer, improviser, and intermedia artist. He holds a PhD in Music Composition from the University of Chicago and recently served as a Research Fellow in Creative Coding at the University of Huddersfield, investigating the creative affordances of machine learning and data science algorithms as part of the FluCoMa project. His work focuses on fusing the sonic, visual, physical, and acoustic aspects of performance and sound, often through the integration of technology.
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