Machine Learning as Creative Tool for Designing Real-Time Expressive Interactions

Supervised learning algorithms can be understood not only as a set of techniques for building accurate models of data, but also as design tools that can enable rapid prototyping, iterative refinement, and embodied engagement- all activities that are crucial in the design of new musical instruments and other embodied interactions. Realising the creative potential of these algorithms requires a rethinking of the interfaces through which people provide data and build models, providing for tight interaction-feedback loops and efficient mechanisms for people to steer and explore algorithm behaviours.

In this talk, I will discuss my research on better enabling composers, musicians, and developers to employ supervised learning in the design of new real-time systems. I will show a live demo of tools that I have created for this purpose, centering around the Wekinator software toolkit for interactive machine learning. I’ll discuss some of the outcomes from 6 years of employing and observing others using machine learning in creative contexts. These include a better understanding how machine learning can be used as a tool for design by end users and developers, and how using machine learning as a design tool differs from more conventional application contexts.

Speaker Details

Dr. Rebecca Fiebrink is a Lecturer at Goldsmiths, University of London. Her research focuses on designing new ways for humans to interact with computers in creative practice, including on the use of machine learning as a creative tool. Fiebrink is the developer of the Wekinator system for real-time interactive machine learning (with a new version just released in 2015!), a co-creator of the Digital Fauvel platform for interactive musicology, and a Co-I on the £1.6M Horizon 2020-funded RAPID-MIX project on Real-time Adaptive Prototyping for Industrial Design of Multimodal Expressive Technology. She is the creator of a MOOC titled “Machine Learning for Artists and Musicians,” launching in early 2016 on the Kadenze platform. She was previously an Assistant Professor at Princeton University, where she co-directed the Princeton Laptop Orchestra. She has worked with companies including Microsoft Research, Sun Microsystems Research Labs, Imagine Research, and Smule, where she helped to build the #1 iTunes app “I am T-Pain.” She holds a PhD in Computer Science from Princeton University.

Series:
Microsoft Research Talks
Date:
Speakers:
Rebecca Fiebrink
Affiliation:
Goldsmiths, University of London

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Series: Microsoft Research Talks