Live Interfaces Journal

Touch the Screen, Wild the Sound: Expressive iPad Performance in Nature

David Rothenberg — 2025-02-26

Although the touch-screen interface on the iPad is often derided as an interface for live music-making, there is something uniquely satisfying about it when played with certain apps designed to take advantage of its unpredictability. This essay emphasises what makes each of those apps favourable to playing live, especially outdoors along with electronic-sounding plants and animals heard underwater in rivers and ponds, suggesting how different species respond to these kinds of indeterminate sounds. It articulates a tentative aesthetics of touch-screen electronic performance in and with the sounds of nature.

The Interface as Artwork: Creating Interactive Installations Based on Encounter and Somatic Experience

Marie-Eve Morissette — 2025-02-26

This media-rich article emphasises the role of the body in aesthetic experience, using a related conceptual framework to explore interfaces in digital art. We introduce two interactive installations, ON/CONTACT and EN/GLOBE, which invite audiences to experience the interface as a site of encounter. To frame the concept of the interface as a device that transcends functional control, we draw on the theoretical work of David Rokeby, a contemporary Canadian artist. In doing so, we demonstrate how our multimodal installations – which engage vision, audition and haptics – encourage participants to interact and express themselves, highlighting the interface’s potential as an agent of exploration rather than mere functional subordination.

Editing Video Streams Through Natural Language Embeddings: Keyframe Sequencing Using Transformers

Luís Arandas — 2025-02-26

The automation of video editing processes with artificial intelligence (AI) is a flourishing field of research, whether the purpose is to save labour, or motivate the emergence of unexpected ideas. Informed by theories on human-like reasoning, problem-solving and learning, these technologies can produce video sequences without much human intervention. In this article we showcase the design and implementation of a system that sequences video datasets based on semantic correlations with natural language. Our system generates videos automatically with tractable principles for montage, removing the human editor – if and when they want – from the process of individual element selection.